Search results for: error matrices
1668 Movie Genre Preference Prediction Using Machine Learning for Customer-Based Information
Authors: Haifeng Wang, Haili Zhang
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Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.Keywords: computational social science, movie preference, machine learning, SVM
Procedia PDF Downloads 2511667 Air Quality Forecast Based on Principal Component Analysis-Genetic Algorithm and Back Propagation Model
Authors: Bin Mu, Site Li, Shijin Yuan
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Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model
Procedia PDF Downloads 2181666 Some Efficient Higher Order Iterative Schemes for Solving Nonlinear Systems
Authors: Sandeep Singh
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In this article, two classes of iterative schemes are proposed for approximating solutions of nonlinear systems of equations whose orders of convergence are six and eight respectively. Sixth order scheme requires the evaluation of two vector-functions, two first Fr'echet derivatives and three matrices inversion per iteration. This three-step sixth-order method is further extended to eighth-order method which requires one more step and the evaluation of one extra vector-function. Moreover, computational efficiency is compared with some other recently published methods in which we found, our methods are more efficient than existing numerical methods for higher and medium size nonlinear system of equations. Numerical tests are performed to validate the proposed schemes.Keywords: Nonlinear systems, Computational complexity, order of convergence, Jarratt-type scheme
Procedia PDF Downloads 1281665 Performance Comparison of Joint Diagonalization Structure (JDS) Method and Wideband MUSIC Method
Authors: Sandeep Santosh, O. P. Sahu
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We simulate an efficient multiple wideband and nonstationary source localization algorithm by exploiting both the non-stationarity of the signals and the array geometric information.This algorithm is based on joint diagonalization structure (JDS) of a set of short time power spectrum matrices at different time instants of each frequency bin. JDS can be used for quick and accurate multiple non-stationary source localization. The JDS algorithm is a one stage process i.e it directly searches the Direction of arrivals (DOAs) over the continuous location parameter space. The JDS method requires that the number of sensors is not less than the number of sources. By observing the simulation results, one can conclude that the JDS method can localize two sources when their difference is not less than 7 degree but the Wideband MUSIC is able to localize two sources for difference of 18 degree.Keywords: joint diagonalization structure (JDS), wideband direction of arrival (DOA), wideband MUSIC
Procedia PDF Downloads 4611664 Valorization of Banana Peels for Mercury Removal in Environmental Realist Conditions
Authors: E. Fabre, C. Vale, E. Pereira, C. M. Silva
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Introduction: Mercury is one of the most troublesome toxic metals responsible for the contamination of the aquatic systems due to its accumulation and bioamplification along the food chain. The 2030 agenda for sustainable development of United Nations promotes the improving of water quality by reducing water pollution and foments an enhance in wastewater treatment, encouraging their recycling and safe water reuse globally. Sorption processes are widely used in wastewater treatments due to their many advantages such as high efficiency and low operational costs. In these processes the target contaminant is removed from the solution by a solid sorbent. The more selective and low cost is the biosorbent the more attractive becomes the process. Agricultural wastes are especially attractive approaches for sorption. They are largely available, have no commercial value and require little or no processing. In this work, banana peels were tested for mercury removal from low concentrated solutions. In order to investigate the applicability of this solid, six water matrices were used increasing the complexity from natural waters to a real wastewater. Studies of kinetics and equilibrium were also performed using the most known models to evaluate the viability of the process In line with the concept of circular economy, this study adds value to this by-product as well as contributes to liquid waste management. Experimental: The solutions were prepared with Hg(II) initial concentration of 50 µg L-1 in natural waters, at 22 ± 1 ºC, pH 6, magnetically stirring at 650 rpm and biosorbent mass of 0.5 g L-1. NaCl was added to obtain the salt solutions, seawater was collected from the Portuguese coast and the real wastewater was kindly provided by ISQ - Instituto de Soldadura e qualidade (Welding and Quality Institute) and diluted until the same concentration of 50 µg L-1. Banana peels were previously freeze-drying, milled, sieved and the particles < 1 mm were used. Results: Banana peels removed more than 90% of Hg(II) from all the synthetic solutions studied. In these cases, the enhance in the complexity of the water type promoted a higher mercury removal. In salt waters, the biosorbent showed removals of 96%, 95% and 98 % for 3, 15 and 30 g L-1 of NaCl, respectively. The residual concentration of Hg(II) in solution achieved the level of drinking water regulation (1 µg L-1). For real matrices, the lower Hg(II) elimination (93 % for seawater and 81 % for the real wastewaters), can be explained by the competition between the Hg(II) ions and the other elements present in these solutions for the sorption sites. Regarding the equilibrium study, the experimental data are better described by the Freundlich isotherm (R ^ 2=0.991). The Elovich equation provided the best fit to the kinetic points. Conclusions: The results exhibited the great ability of the banana peels to remove mercury. The environmental realist conditions studied in this work, highlight their potential usage as biosorbents in water remediation processes.Keywords: banana peels, mercury removal, sorption, water treatment
Procedia PDF Downloads 1461663 An Observer-Based Direct Adaptive Fuzzy Sliding Control with Adjustable Membership Functions
Authors: Alireza Gholami, Amir H. D. Markazi
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In this paper, an observer-based direct adaptive fuzzy sliding mode (OAFSM) algorithm is proposed. In the proposed algorithm, the zero-input dynamics of the plant could be unknown. The input connection matrix is used to combine the sliding surfaces of individual subsystems, and an adaptive fuzzy algorithm is used to estimate an equivalent sliding mode control input directly. The fuzzy membership functions, which were determined by time consuming try and error processes in previous works, are adjusted by adaptive algorithms. The other advantage of the proposed controller is that the input gain matrix is not limited to be diagonal, i.e. the plant could be over/under actuated provided that controllability and observability are preserved. An observer is constructed to directly estimate the state tracking error, and the nonlinear part of the observer is constructed by an adaptive fuzzy algorithm. The main advantage of the proposed observer is that, the measured outputs is not limited to the first entry of a canonical-form state vector. The closed-loop stability of the proposed method is proved using a Lyapunov-based approach. The proposed method is applied numerically on a multi-link robot manipulator, which verifies the performance of the closed-loop control. Moreover, the performance of the proposed algorithm is compared with some conventional control algorithms.Keywords: adaptive algorithm, fuzzy systems, membership functions, observer
Procedia PDF Downloads 1981662 Development of a General Purpose Computer Programme Based on Differential Evolution Algorithm: An Application towards Predicting Elastic Properties of Pavement
Authors: Sai Sankalp Vemavarapu
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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation
Procedia PDF Downloads 1581661 Evaluation of Ceres Wheat and Rice Model for Climatic Conditions in Haryana, India
Authors: Mamta Rana, K. K. Singh, Nisha Kumari
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The simulation models with its soil-weather-plant atmosphere interacting system are important tools for assessing the crops in changing climate conditions. The CERES-Wheat & Rice vs. 4.6 DSSAT was calibrated and evaluated for one of the major producers of wheat and rice state- Haryana, India. The simulation runs were made under irrigated conditions and three fertilizer applications dose of N-P-K to estimate crop yield and other growth parameters along with the phenological development of the crop. The genetic coefficients derived by iteratively manipulating the relevant coefficients that characterize the phenological process of wheat and rice crop to the best fit match between the simulated and observed anthesis, physological maturity and final grain yield. The model validated by plotting the simulated and remote sensing derived LAI. LAI product from remote sensing provides the edge of spatial, timely and accurate assessment of crop. For validating the yield and yield components, the error percentage between the observed and simulated data was calculated. The analysis shows that the model can be used to simulate crop yield and yield components for wheat and rice cultivar under different management practices. During the validation, the error percentage was less than 10%, indicating the utility of the calibrated model for climate risk assessment in the selected region.Keywords: simulation model, CERES-wheat and rice model, crop yield, genetic coefficient
Procedia PDF Downloads 2971660 A Geo DataBase to Investigate the Maximum Distance Error in Quality of Life Studies
Authors: Paolino Di Felice
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The background and significance of this study come from papers already appeared in the literature which measured the impact of public services (e.g., hospitals, schools, ...) on the citizens’ needs satisfaction (one of the dimensions of QOL studies) by calculating the distance between the place where they live and the location on the territory of the services. Those studies assume that the citizens' dwelling coincides with the centroid of the polygon that expresses the boundary of the administrative district, within the city, they belong to. Such an assumption “introduces a maximum measurement error equal to the greatest distance between the centroid and the border of the administrative district.”. The case study, this abstract reports about, investigates the implications descending from the adoption of such an approach but at geographical scales greater than the urban one, namely at the three levels of nesting of the Italian administrative units: the (20) regions, the (110) provinces, and the 8,094 municipalities. To carry out this study, it needs to be decided: a) how to store the huge amount of (spatial and descriptive) input data and b) how to process them. The latter aspect involves: b.1) the design of algorithms to investigate the geometry of the boundary of the Italian administrative units; b.2) their coding in a programming language; b.3) their execution and, eventually, b.4) archiving the results in a permanent support. The IT solution we implemented is centered around a (PostgreSQL/PostGIS) Geo DataBase structured in terms of three tables that fit well to the hierarchy of nesting of the Italian administrative units: municipality(id, name, provinceId, istatCode, regionId, geometry) province(id, name, regionId, geometry) region(id, name, geometry). The adoption of the DBMS technology allows us to implement the steps "a)" and "b)" easily. In particular, step "b)" is simplified dramatically by calling spatial operators and spatial built-in User Defined Functions within SQL queries against the Geo DB. The major findings coming from our experiments can be summarized as follows. The approximation that, on the average, descends from assimilating the residence of the citizens with the centroid of the administrative unit of reference is of few kilometers (4.9) at the municipalities level, while it becomes conspicuous at the other two levels (28.9 and 36.1, respectively). Therefore, studies such as those mentioned above can be extended up to the municipal level without affecting the correctness of the interpretation of the results, but not further. The IT framework implemented to carry out the experiments can be replicated for studies referring to the territory of other countries all over the world.Keywords: quality of life, distance measurement error, Italian administrative units, spatial database
Procedia PDF Downloads 3671659 Forward Stable Computation of Roots of Real Polynomials with Only Real Distinct Roots
Authors: Nevena Jakovčević Stor, Ivan Slapničar
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Any polynomial can be expressed as a characteristic polynomial of a complex symmetric arrowhead matrix. This expression is not unique. If the polynomial is real with only real distinct roots, the matrix can be chosen as real. By using accurate forward stable algorithm for computing eigen values of real symmetric arrowhead matrices we derive a forward stable algorithm for computation of roots of such polynomials in O(n^2 ) operations. The algorithm computes each root to almost full accuracy. In some cases, the algorithm invokes extended precision routines, but only in the non-iterative part. Our examples include numerically difficult problems, like the well-known Wilkinson’s polynomials. Our algorithm compares favorably to other method for polynomial root-finding, like MPSolve or Newton’s method.Keywords: roots of polynomials, eigenvalue decomposition, arrowhead matrix, high relative accuracy
Procedia PDF Downloads 4101658 Localization of Buried People Using Received Signal Strength Indication Measurement of Wireless Sensor
Authors: Feng Tao, Han Ye, Shaoyi Liao
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City constructions collapse after earthquake and people will be buried under ruins. Search and rescue should be conducted as soon as possible to save them. Therefore, according to the complicated environment, irregular aftershocks and rescue allow of no delay, a kind of target localization method based on RSSI (Received Signal Strength Indication) is proposed in this article. The target localization technology based on RSSI with the features of low cost and low complexity has been widely applied to nodes localization in WSN (Wireless Sensor Networks). Based on the theory of RSSI transmission and the environment impact to RSSI, this article conducts the experiments in five scenes, and multiple filtering algorithms are applied to original RSSI value in order to establish the signal propagation model with minimum test error respectively. Target location can be calculated from the distance, which can be estimated from signal propagation model, through improved centroid algorithm. Result shows that the localization technology based on RSSI is suitable for large-scale nodes localization. Among filtering algorithms, mixed filtering algorithm (average of average, median and Gaussian filtering) performs better than any other single filtering algorithm, and by using the signal propagation model, the minimum error of distance between known nodes and target node in the five scene is about 3.06m.Keywords: signal propagation model, centroid algorithm, localization, mixed filtering, RSSI
Procedia PDF Downloads 2931657 Classification of Barley Varieties by Artificial Neural Networks
Authors: Alper Taner, Yesim Benal Oztekin, Huseyin Duran
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In this study, an Artificial Neural Network (ANN) was developed in order to classify barley varieties. For this purpose, physical properties of barley varieties were determined and ANN techniques were used. The physical properties of 8 barley varieties grown in Turkey, namely thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain, were determined and it was found that these properties were statistically significant with respect to varieties. As ANN model, three models, N-l, N-2 and N-3 were constructed. The performances of these models were compared. It was determined that the best-fit model was N-1. In the N-1 model, the structure of the model was designed to be 11 input layers, 2 hidden layers and 1 output layer. Thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain were used as input parameter; and varieties as output parameter. R2, Root Mean Square Error and Mean Error for the N-l model were found as 99.99%, 0.00074 and 0.009%, respectively. All results obtained by the N-l model were observed to have been quite consistent with real data. By this model, it would be possible to construct automation systems for classification and cleaning in flourmills.Keywords: physical properties, artificial neural networks, barley, classification
Procedia PDF Downloads 1751656 Of an 80 Gbps Passive Optical Network Using Time and Wavelength Division Multiplexing
Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Faizan Khan, Xiaodong Yang
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Internet Service Providers are driving endless demands for higher bandwidth and data throughput as new services and applications require higher bandwidth. Users want immediate and accurate data delivery. This article focuses on converting old conventional networks into passive optical networks based on time division and wavelength division multiplexing. The main focus of this research is to use a hybrid of time-division multiplexing and wavelength-division multiplexing to improve network efficiency and performance. In this paper, we design an 80 Gbps Passive Optical Network (PON), which meets the need of the Next Generation PON Stage 2 (NGPON2) proposed in this paper. The hybrid of the Time and Wavelength division multiplexing (TWDM) is said to be the best solution for the implementation of NGPON2, according to Full-Service Access Network (FSAN). To co-exist with or replace the current PON technologies, many wavelengths of the TWDM can be implemented simultaneously. By utilizing 8 pairs of wavelengths that are multiplexed and then transmitted over optical fiber for 40 Kms and on the receiving side, they are distributed among 256 users, which shows that the solution is reliable for implementation with an acceptable data rate. From the results, it can be concluded that the overall performance, Quality Factor, and bandwidth of the network are increased, and the Bit Error rate is minimized by the integration of this approach.Keywords: bit error rate, fiber to the home, passive optical network, time and wavelength division multiplexing
Procedia PDF Downloads 641655 Impact Position Method Based on Distributed Structure Multi-Agent Coordination with JADE
Authors: YU Kaijun, Liang Dong, Zhang Yarong, Jin Zhenzhou, Yang Zhaobao
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For the impact monitoring of distributed structures, the traditional positioning methods are based on the time difference, which includes the four-point arc positioning method and the triangulation positioning method. But in the actual operation, these two methods have errors. In this paper, the Multi-Agent Blackboard Coordination Principle is used to combine the two methods. Fusion steps: (1) The four-point arc locating agent calculates the initial point and records it to the Blackboard Module.(2) The triangulation agent gets its initial parameters by accessing the initial point.(3) The triangulation agent constantly accesses the blackboard module to update its initial parameters, and it also logs its calculated point into the blackboard.(4) When the subsequent calculation point and the initial calculation point are within the allowable error, the whole coordination fusion process is finished. This paper presents a Multi-Agent collaboration method whose agent framework is JADE. The JADE platform consists of several agent containers, with the agent running in each container. Because of the perfect management and debugging tools of the JADE, it is very convenient to deal with complex data in a large structure. Finally, based on the data in Jade, the results show that the impact location method based on Multi-Agent coordination fusion can reduce the error of the two methods.Keywords: impact monitoring, structural health monitoring(SHM), multi-agent system(MAS), black-board coordination, JADE
Procedia PDF Downloads 1711654 Relationship between Electricity Consumption and Economic Growth: Evidence from Nigeria (1971-2012)
Authors: N. E Okoligwe, Okezie A. Ihugba
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Few scholars disagrees that electricity consumption is an important supporting factor for economy growth. However, the relationship between electricity consumption and economy growth has different manifestation in different countries according to previous studies. This paper examines the causal relationship between electricity consumption and economic growth for Nigeria. In an attempt to do this, the paper tests the validity of the modernization or depending hypothesis by employing various econometric tools such as Augmented Dickey Fuller (ADF) and Johansen Co-integration test, the Error Correction Mechanism (ECM) and Granger Causality test on time series data from 1971-2012. The Granger causality is found not to run from electricity consumption to real GDP and from GDP to electricity consumption during the year of study. The null hypothesis is accepted at the 5 per cent level of significance where the probability value (0.2251 and 0.8251) is greater than five per cent level of significance because both of them are probably determined by some other factors like; increase in urban population, unemployment rate and the number of Nigerians that benefit from the increase in GDP and increase in electricity demand is not determined by the increase in GDP (income) over the period of study because electricity demand has always been greater than consumption. Consequently; the policy makers in Nigeria should place priority in early stages of reconstruction on building capacity additions and infrastructure development of the electric power sector as this would force the sustainable economic growth in Nigeria.Keywords: economic growth, electricity consumption, error correction mechanism, granger causality test
Procedia PDF Downloads 3011653 Research on Pilot Sequence Design Method of Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing System Based on High Power Joint Criterion
Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang
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For the pilot design of the sparse channel estimation model in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the observation matrix constructed according to the matrix cross-correlation criterion, total correlation criterion and other optimization criteria are not optimal, resulting in inaccurate channel estimation and high bit error rate at the receiver. This paper proposes a pilot design method combining high-power sum and high-power variance criteria, which can more accurately estimate the channel. First, the pilot insertion position is designed according to the high-power variance criterion under the condition of equal power. Then, according to the high power sum criterion, the pilot power allocation is converted into a cone programming problem, and the power allocation is carried out. Finally, the optimal pilot is determined by calculating the weighted sum of the high power sum and the high power variance. Compared with the traditional pilot frequency, under the same conditions, the constructed MIMO-OFDM system uses the optimal pilot frequency for channel estimation, and the communication bit error rate performance obtains a gain of 6~7dB.Keywords: MIMO-OFDM, pilot optimization, compressed sensing, channel estimation
Procedia PDF Downloads 1411652 Usage the Point Analysis Algorithm (SANN) on Drought Analysis
Authors: Khosro Shafie Motlaghi, Amir Reza Salemian
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In arid and semi-arid regions like our country Evapotranspiration is the greatestportion of water resource. Therefor knowlege of its changing and other climate parameters plays an important role for planning, development, and management of water resource. In this search the Trend of long changing of Evapotranspiration (ET0), average temprature, monthly rainfall were tested. To dose, all synoptic station s in iran were divided according to the climate with Domarton climate. The present research was done in semi-arid climate of Iran, and in which 14 synoptic with 30 years period of statistics were investigated with 3 methods of minimum square error, Mann Kendoll, and Vald-Volfoytz Evapotranspiration was calculated by using the method of FAO-Penman. The results of investigation in periods of statistic has shown that the process Evapotranspiration parameter of 24 percent of stations is positive, and for 2 percent is negative, and for 47 percent. It was without any Trend. Similary for 22 percent of stations was positive the Trend of parameter of temperature for 19 percent , the trend was negative and for 64 percent, it was without any Trend. The results of rainfall trend has shown that the amount of rainfall in most stations was not considered as a meaningful trend. The result of Mann-kendoll method similar to minimum square error method. regarding the acquired result was can admit that in future years Some regions will face increase of temperature and Evapotranspiration.Keywords: analysis, algorithm, SANN, ET0
Procedia PDF Downloads 2921651 Error Analysis of Pronunciation of French by Sinhala Speaking Learners
Authors: Chandeera Gunawardena
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The present research analyzes the pronunciation errors encountered by thirty Sinhala speaking learners of French on the assumption that the pronunciation errors were systematic and they reflect the interference of the native language of the learners. The thirty participants were selected using random sampling method. By the time of the study, the subjects were studying French as a foreign language for their Bachelor of Arts Degree at University of Kelaniya, Sri Lanka. The participants were from a homogenous linguistics background. All participants speak the same native language (Sinhala) thus they had completed their secondary education in Sinhala medium and during which they had also learnt French as a foreign language. A battery operated audio tape recorder and a 120-minute blank cassettes were used for recording. A list comprised of 60 words representing all French phonemes was used to diagnose pronunciation difficulties. Before the recording process commenced, the subjects were requested to familiarize themselves with the words through reading them several times. The recording was conducted individually in a quiet classroom and each recording approximately took fifteen minutes. Each subject was required to read at a normal speed. After the completion of recording, the recordings were replayed to identify common errors which were immediately transcribed using the International Phonetic Alphabet. Results show that Sinhala speaking learners face problems with French nasal vowels and French initial consonants clusters. The learners also exhibit errors which occur because of their second language (English) interference.Keywords: error analysis, pronunciation difficulties, pronunciation errors, Sinhala speaking learners of French
Procedia PDF Downloads 2051650 A Comparative Study of Sampling-Based Uncertainty Propagation with First Order Error Analysis and Percentile-Based Optimization
Authors: M. Gulam Kibria, Shourav Ahmed, Kais Zaman
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In system analysis, the information on the uncertain input variables cause uncertainty in the system responses. Different probabilistic approaches for uncertainty representation and propagation in such cases exist in the literature. Different uncertainty representation approaches result in different outputs. Some of the approaches might result in a better estimation of system response than the other approaches. The NASA Langley Multidisciplinary Uncertainty Quantification Challenge (MUQC) has posed challenges about uncertainty quantification. Subproblem A, the uncertainty characterization subproblem, of the challenge posed is addressed in this study. In this subproblem, the challenge is to gather knowledge about unknown model inputs which have inherent aleatory and epistemic uncertainties in them with responses (output) of the given computational model. We use two different methodologies to approach the problem. In the first methodology we use sampling-based uncertainty propagation with first order error analysis. In the other approach we place emphasis on the use of Percentile-Based Optimization (PBO). The NASA Langley MUQC’s subproblem A is developed in such a way that both aleatory and epistemic uncertainties need to be managed. The challenge problem classifies each uncertain parameter as belonging to one the following three types: (i) An aleatory uncertainty modeled as a random variable. It has a fixed functional form and known coefficients. This uncertainty cannot be reduced. (ii) An epistemic uncertainty modeled as a fixed but poorly known physical quantity that lies within a given interval. This uncertainty is reducible. (iii) A parameter might be aleatory but sufficient data might not be available to adequately model it as a single random variable. For example, the parameters of a normal variable, e.g., the mean and standard deviation, might not be precisely known but could be assumed to lie within some intervals. It results in a distributional p-box having the physical parameter with an aleatory uncertainty, but the parameters prescribing its mathematical model are subjected to epistemic uncertainties. Each of the parameters of the random variable is an unknown element of a known interval. This uncertainty is reducible. From the study, it is observed that due to practical limitations or computational expense, the sampling is not exhaustive in sampling-based methodology. That is why the sampling-based methodology has high probability of underestimating the output bounds. Therefore, an optimization-based strategy to convert uncertainty described by interval data into a probabilistic framework is necessary. This is achieved in this study by using PBO.Keywords: aleatory uncertainty, epistemic uncertainty, first order error analysis, uncertainty quantification, percentile-based optimization
Procedia PDF Downloads 2331649 In-Flight Aircraft Performance Model Enhancement Using Adaptive Lookup Tables
Authors: Georges Ghazi, Magali Gelhaye, Ruxandra Botez
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Over the years, the Flight Management System (FMS) has experienced a continuous improvement of its many features, to the point of becoming the pilot’s primary interface for flight planning operation on the airplane. With the assistance of the FMS, the concept of distance and time has been completely revolutionized, providing the crew members with the determination of the optimized route (or flight plan) from the departure airport to the arrival airport. To accomplish this function, the FMS needs an accurate Aircraft Performance Model (APM) of the aircraft. In general, APMs that equipped most modern FMSs are established before the entry into service of an individual aircraft, and results from the combination of a set of ordinary differential equations and a set of performance databases. Unfortunately, an aircraft in service is constantly exposed to dynamic loads that degrade its flight characteristics. These degradations endow two main origins: airframe deterioration (control surfaces rigging, seals missing or damaged, etc.) and engine performance degradation (fuel consumption increase for a given thrust). Thus, after several years of service, the performance databases and the APM associated to a specific aircraft are no longer representative enough of the actual aircraft performance. It is important to monitor the trend of the performance deterioration and correct the uncertainties of the aircraft model in order to improve the accuracy the flight management system predictions. The basis of this research lies in the new ability to continuously update an Aircraft Performance Model (APM) during flight using an adaptive lookup table technique. This methodology was developed and applied to the well-known Cessna Citation X business aircraft. For the purpose of this study, a level D Research Aircraft Flight Simulator (RAFS) was used as a test aircraft. According to Federal Aviation Administration the level D is the highest certification level for the flight dynamics modeling. Basically, using data available in the Flight Crew Operating Manual (FCOM), a first APM describing the variation of the engine fan speed and aircraft fuel flow w.r.t flight conditions was derived. This model was next improved using the proposed methodology. To do that, several cruise flights were performed using the RAFS. An algorithm was developed to frequently sample the aircraft sensors measurements during the flight and compare the model prediction with the actual measurements. Based on these comparisons, a correction was performed on the actual APM in order to minimize the error between the predicted data and the measured data. In this way, as the aircraft flies, the APM will be continuously enhanced, making the FMS more and more precise and the prediction of trajectories more realistic and more reliable. The results obtained are very encouraging. Indeed, using the tables initialized with the FCOM data, only a few iterations were needed to reduce the fuel flow prediction error from an average relative error of 12% to 0.3%. Similarly, the FCOM prediction regarding the engine fan speed was reduced from a maximum error deviation of 5.0% to 0.2% after only ten flights.Keywords: aircraft performance, cruise, trajectory optimization, adaptive lookup tables, Cessna Citation X
Procedia PDF Downloads 2581648 An Application of Vector Error Correction Model to Assess Financial Innovation Impact on Economic Growth of Bangladesh
Authors: Md. Qamruzzaman, Wei Jianguo
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Over the decade, it is observed that financial development, through financial innovation, not only accelerated development of efficient and effective financial system but also act as a catalyst in the economic development process. In this study, we try to explore insight about how financial innovation causes economic growth in Bangladesh by using Vector Error Correction Model (VECM) for the period of 1990-2014. Test of Cointegration confirms the existence of a long-run association between financial innovation and economic growth. For investigating directional causality, we apply Granger causality test and estimation explore that long-run growth will be affected by capital flow from non-bank financial institutions and inflation in the economy but changes of growth rate do not have any impact on Capital flow in the economy and level of inflation in long-run. Whereas, growth and Market capitalization, as well as market capitalization and capital flow, confirm feedback hypothesis. Variance decomposition suggests that any innovation in the financial sector can cause GDP variation fluctuation in both long run and short run. Financial innovation promotes efficiency and cost in financial transactions in the financial system, can boost economic development process. The study proposed two policy recommendations for further development. First, innovation friendly financial policy should formulate to encourage adaption and diffusion of financial innovation in the financial system. Second, operation of financial market and capital market should be regulated with implementation of rules and regulation to create conducive environment.Keywords: financial innovation, economic growth, GDP, financial institution, VECM
Procedia PDF Downloads 2621647 Neural Network Models for Actual Cost and Actual Duration Estimation in Construction Projects: Findings from Greece
Authors: Panagiotis Karadimos, Leonidas Anthopoulos
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Predicting the actual cost and duration in construction projects concern a continuous and existing problem for the construction sector. This paper addresses this problem with modern methods and data available from past public construction projects. 39 bridge projects, constructed in Greece, with a similar type of available data were examined. Considering each project’s attributes with the actual cost and the actual duration, correlation analysis is performed and the most appropriate predictive project variables are defined. Additionally, the most efficient subgroup of variables is selected with the use of the WEKA application, through its attribute selection function. The selected variables are used as input neurons for neural network models through correlation analysis. For constructing neural network models, the application FANN Tool is used. The optimum neural network model, for predicting the actual cost, produced a mean squared error with a value of 3.84886e-05 and it was based on the budgeted cost and the quantity of deck concrete. The optimum neural network model, for predicting the actual duration, produced a mean squared error with a value of 5.89463e-05 and it also was based on the budgeted cost and the amount of deck concrete.Keywords: actual cost and duration, attribute selection, bridge construction, neural networks, predicting models, FANN TOOL, WEKA
Procedia PDF Downloads 1271646 Further Analysis of Global Robust Stability of Neural Networks with Multiple Time Delays
Authors: Sabri Arik
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In this paper, we study the global asymptotic robust stability of delayed neural networks with norm-bounded uncertainties. By employing the Lyapunov stability theory and Homeomorphic mapping theorem, we derive some new types of sufficient conditions ensuring the existence, uniqueness and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delays under parameter uncertainties and with respect to continuous and slopebounded activation functions. An important aspect of our results is their low computational complexity as the reported results can be verified by checking some properties symmetric matrices associated with the uncertainty sets of network parameters. The obtained results are shown to be generalization of some of the previously published corresponding results. Some comparative numerical examples are also constructed to compare our results with some closely related existing literature results.Keywords: neural networks, delayed systems, lyapunov functionals, stability analysis
Procedia PDF Downloads 5201645 A Comparative Study of Optimization Techniques and Models to Forecasting Dengue Fever
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Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.Keywords: deep learning model, dengue fever, prediction, optimization
Procedia PDF Downloads 541644 Efficient Pre-Processing of Single-Cell Assay for Transposase Accessible Chromatin with High-Throughput Sequencing Data
Authors: Fan Gao, Lior Pachter
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The primary tool currently used to pre-process 10X Chromium single-cell ATAC-seq data is Cell Ranger, which can take very long to run on standard datasets. To facilitate rapid pre-processing that enables reproducible workflows, we present a suite of tools called scATAK for pre-processing single-cell ATAC-seq data that is 15 to 18 times faster than Cell Ranger on mouse and human samples. Our tool can also calculate chromatin interaction potential matrices, and generate open chromatin signal and interaction traces for cell groups. We use scATAK tool to explore the chromatin regulatory landscape of a healthy adult human brain and unveil cell-type specific features, and show that it provides a convenient and computational efficient approach for pre-processing single-cell ATAC-seq data.Keywords: single-cell, ATAC-seq, bioinformatics, open chromatin landscape, chromatin interactome
Procedia PDF Downloads 1511643 Performance Analysis of Geophysical Database Referenced Navigation: The Combination of Gravity Gradient and Terrain Using Extended Kalman Filter
Authors: Jisun Lee, Jay Hyoun Kwon
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As an alternative way to compensate the INS (inertial navigation system) error in non-GNSS (Global Navigation Satellite System) environment, geophysical database referenced navigation is being studied. In this study, both gravity gradient and terrain data were combined to complement the weakness of sole geophysical data as well as to improve the stability of the positioning. The main process to compensate the INS error using geophysical database was constructed on the basis of the EKF (Extended Kalman Filter). In detail, two type of combination method, centralized and decentralized filter, were applied to check the pros and cons of its algorithm and to find more robust results. The performance of each navigation algorithm was evaluated based on the simulation by supposing that the aircraft flies with precise geophysical DB and sensors above nine different trajectories. Especially, the results were compared to the ones from sole geophysical database referenced navigation to check the improvement due to a combination of the heterogeneous geophysical database. It was found that the overall navigation performance was improved, but not all trajectories generated better navigation result by the combination of gravity gradient with terrain data. Also, it was found that the centralized filter generally showed more stable results. It is because that the way to allocate the weight for the decentralized filter could not be optimized due to the local inconsistency of geophysical data. In the future, switching of geophysical data or combining different navigation algorithm are necessary to obtain more robust navigation results.Keywords: Extended Kalman Filter, geophysical database referenced navigation, gravity gradient, terrain
Procedia PDF Downloads 3421642 Novel Animal Drawn Wheel-Axle Mechanism Actuated Knapsack Boom Sprayer
Authors: Ibrahim O. Abdulmalik, Michael C. Amonye, Mahdi Makoyo
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Manual knapsack sprayer is the most popular means of farm spraying in Nigeria. It has its limitations. Apart from the human fatigue, which leads to unsteady walking steps, their field capacities are small. They barely cover about 0.2hectare per hour. Their small swath implies that a sizeable farm would take several days to cover. Weather changes are erratic and often it is desired to spray a large farm within hours or few days for even effect, uniformity and to avoid adverse weather interference. It is also often required that a large farm be covered within a short period to avoid re-emergence of weeds before crop emergence. Deployment of many knapsack operators to large farms has not been successful. Human error in taking equally spaced swaths usually result in over dosage of overlaps and in unapplied areas due to error at edges overlaps. Large farm spraying require boom equipment with larger swath. Reduced error in swath overlaps and spraying within the shortest possible time are then assured. Tractor boom sprayers would readily overcome these problems and achieve greater coverage, but they are not available in the country. Tractor hire for cultivation is very costly with the attendant lack of spare parts and specialized technicians for maintenance wherefore farmers find it difficult to engage tractors for cultivation and would avoid considering the employment of a tractor boom sprayer. Animal traction in farming is predominant in Nigeria, especially in the Northern part of the country. Development of boom sprayers drawn by work animals surely implies the maximization of animal utilization in farming. The Hydraulic Equipment Development Institute, Kano, in keeping to its mandate of targeted R&D in hydraulic and pneumatic systems, has developed an Animal Drawn Knapsack Boom Sprayer with four nozzles using the axle mechanism of a two wheeled cart to actuate the piston pump of two knapsack sprayers in line with appropriate technology demand of the country. It is hoped that the introduction of this novel contrivance shall enhance crop protection practice and lead to greater crop and food production in Nigeria.Keywords: boom, knapsack, farm, sprayer, wheel axle
Procedia PDF Downloads 2801641 The Influence of Different Flux Patterns on Magnetic Losses in Electric Machine Cores
Authors: Natheer Alatawneh
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The finite element analysis of magnetic fields in electromagnetic devices shows that the machine cores experience different flux patterns including alternating and rotating fields. The rotating fields are generated in different configurations range between circular and elliptical with different ratios between the major and minor axis of the flux locus. Experimental measurements on electrical steel exposed to different flux patterns disclose different magnetic losses in the samples under test. Consequently, electric machines require special attention during the cores loss calculation process to consider the flux patterns. In this study, a circular rotational single sheet tester is employed to measure the core losses in electric steel sample of M36G29. The sample was exposed to alternating field, circular field, and elliptical fields with axis ratios of 0.2, 0.4, 0.6 and 0.8. The measured data was implemented on 6-4 switched reluctance motor at three different frequencies of interest to the industry as 60 Hz, 400 Hz, and 1 kHz. The results disclose a high margin of error that may occur during the loss calculations if the flux patterns issue is neglected. The error in different parts of the machine associated with considering the flux patterns can be around 50%, 10%, and 2% at 60Hz, 400Hz, and 1 kHz, respectively. The future work will focus on the optimization of machine geometrical shape which has a primary effect on the flux pattern in order to minimize the magnetic losses in machine cores.Keywords: alternating core losses, electric machines, finite element analysis, rotational core losses
Procedia PDF Downloads 2441640 Video Compression Using Contourlet Transform
Authors: Delara Kazempour, Mashallah Abasi Dezfuli, Reza Javidan
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Video compression used for channels with limited bandwidth and storage devices has limited storage capabilities. One of the most popular approaches in video compression is the usage of different transforms. Discrete cosine transform is one of the video compression methods that have some problems such as blocking, noising and high distortion inappropriate effect in compression ratio. wavelet transform is another approach is better than cosine transforms in balancing of compression and quality but the recognizing of curve curvature is so limit. Because of the importance of the compression and problems of the cosine and wavelet transforms, the contourlet transform is most popular in video compression. In the new proposed method, we used contourlet transform in video image compression. Contourlet transform can save details of the image better than the previous transforms because this transform is multi-scale and oriented. This transform can recognize discontinuity such as edges. In this approach we lost data less than previous approaches. Contourlet transform finds discrete space structure. This transform is useful for represented of two dimension smooth images. This transform, produces compressed images with high compression ratio along with texture and edge preservation. Finally, the results show that the majority of the images, the parameters of the mean square error and maximum signal-to-noise ratio of the new method based contourlet transform compared to wavelet transform are improved but in most of the images, the parameters of the mean square error and maximum signal-to-noise ratio in the cosine transform is better than the method based on contourlet transform.Keywords: video compression, contourlet transform, discrete cosine transform, wavelet transform
Procedia PDF Downloads 4351639 Pair Interaction in Transition-Metal Nanoparticles
Authors: Nikolay E. Dubinin
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Pair-interaction approximations allow to consider a different states of condensed matter from a single position. At the same time, description of an effective pair interaction in transition metal is a hard task since the d-electron contribution to the potential energy in this case is non-pairwise in principle. There are a number of models for transition-metal effective pair potentials. Here we use the Wills-Harrison (WH) approach to calculate pair potentials for Fe, Co, and Ni in crystalline, liquid, and nano states. Last is especially interesting since nano particles of pure transition metals immobilized on the dielectric matrices are widely used in different fields of advanced technologies: as carriers and transmitters of information, as an effective catalytic materials, etc. It is found that the minimum of the pair potential is deeper and oscillations are stronger in nano crystalline state in comparison with the liquid and crystalline states for all metals under consideration.Keywords: effective pair potential, nanocrystalline state, transition metal, Wills-Harrison approach
Procedia PDF Downloads 378