Search results for: Normalized least mean square methods
4379 An Overview of Islanding Detection Methods in Photovoltaic Systems
Authors: Wei Yee Teoh, Chee Wei Tan
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The issue of unintentional islanding in PV grid interconnection still remains as a challenge in grid-connected photovoltaic (PV) systems. This paper discusses the overview of popularly used anti-islanding detection methods, practically applied in PV grid-connected systems. Anti-islanding methods generally can be classified into four major groups, which include passive methods, active methods, hybrid methods and communication base methods. Active methods have been the preferred detection technique over the years due to very small non-detected zone (NDZ) in small scale distribution generation. Passive method is comparatively simpler than active method in terms of circuitry and operations. However, it suffers from large NDZ that significantly reduces its performance. Communication base methods inherit the advantages of active and passive methods with reduced drawbacks. Hybrid method which evolved from the combination of both active and passive methods has been proven to achieve accurate anti-islanding detection by many researchers. For each of the studied anti-islanding methods, the operation analysis is described while the advantages and disadvantages are compared and discussed. It is difficult to pinpoint a generic method for a specific application, because most of the methods discussed are governed by the nature of application and system dependent elements. This study concludes that the setup and operation cost is the vital factor for anti-islanding method selection in order to achieve minimal compromising between cost and system quality.Keywords: Active method, hybrid method, islanding detection, passive method, photovoltaic (PV), utility method
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 97594378 Time Series Forecasting Using Various Deep Learning Models
Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan
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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed length window in the past as an explicit input. In this paper, we study how the performance of predictive models change as a function of different look-back window sizes and different amounts of time to predict into the future. We also consider the performance of the recent attention-based transformer models, which had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (Recurrent Neural Network (RNN), Long Short-term Memory (LSTM), Gated Recurrent Units (GRU), and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the website of University of California, Irvine (UCI), which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Absolute Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.
Keywords: Air quality prediction, deep learning algorithms, time series forecasting, look-back window.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11674377 A Comparison of Inflow Generation Methods for Large-Eddy Simulation
Authors: Francois T. Pronk, Steven J. Hulshoff
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A study of various turbulent inflow generation methods was performed to compare their relative effectiveness for LES computations of turbulent boundary layers. This study confirmed the quality of the turbulent information produced by the family of recycling and rescaling methods which take information from within the computational domain. Furthermore, more general inflow methods also proved applicable to such simulations, with a precursor-like inflow and a random inflow augmented with forcing planes showing promising results.Keywords: Boundary layer, Flat plate, Inflow modeling, LES
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16634376 Numerical Methods versus Bjerksund and Stensland Approximations for American Options Pricing
Authors: Marasovic Branka, Aljinovic Zdravka, Poklepovic Tea
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Numerical methods like binomial and trinomial trees and finite difference methods can be used to price a wide range of options contracts for which there are no known analytical solutions. American options are the most famous of that kind of options. Besides numerical methods, American options can be valued with the approximation formulas, like Bjerksund-Stensland formulas from 1993 and 2002. When the value of American option is approximated by Bjerksund-Stensland formulas, the computer time spent to carry out that calculation is very short. The computer time spent using numerical methods can vary from less than one second to several minutes or even hours. However to be able to conduct a comparative analysis of numerical methods and Bjerksund-Stensland formulas, we will limit computer calculation time of numerical method to less than one second. Therefore, we ask the question: Which method will be most accurate at nearly the same computer calculation time?
Keywords: Bjerksund and Stensland approximations, Computational analysis, Finance, Options pricing, Numerical methods.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 60674375 Impact of Customer Management System in Improving Customer Retention: Optimization of Negative Customer Feedback
Authors: Alireza Faed, David Forbes
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Complaints today have the ability to retain customer loyalty using state of the art systems and strategies in customer relationship management to analyze and respond to a plethora of customer perception. The Majority of companies are not aware of the beneficiary utilization of customer complaints for the sake of quality improvements. Also, some companies have problems determining how resolution of complaints can be profitable. In this study, we will define the problems and ascertain the importance of customer management system on the companies. Furthermore, we will determine the impact of such a system on efficiency, confidence, profitability and customer complaints. Eventually, we will develop methods and address the issues. In this paper, we used an open-ended questionnaire and distributed that to 30 randomly chosen respondents which were the passengers in an airport. We also define three hypotheses for our study and we will validate each of them. Then using frequency, Chi- Square and quality control method we optimized the size of customers- negative feedback and improved the process of customer retention.Keywords: Complaint, Complaint management system, Customer relationship management, Retention.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23304374 Modeling of Reinforcement in Concrete Beams Using Machine Learning Tools
Authors: Yogesh Aggarwal
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The paper discusses the results obtained to predict reinforcement in singly reinforced beam using Neural Net (NN), Support Vector Machines (SVM-s) and Tree Based Models. Major advantage of SVM-s over NN is of minimizing a bound on the generalization error of model rather than minimizing a bound on mean square error over the data set as done in NN. Tree Based approach divides the problem into a small number of sub problems to reach at a conclusion. Number of data was created for different parameters of beam to calculate the reinforcement using limit state method for creation of models and validation. The results from this study suggest a remarkably good performance of tree based and SVM-s models. Further, this study found that these two techniques work well and even better than Neural Network methods. A comparison of predicted values with actual values suggests a very good correlation coefficient with all four techniques.Keywords: Linear Regression, M5 Model Tree, Neural Network, Support Vector Machines.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20354373 Thrust Enhancement on a Two Dimensional Elliptic Airfoil in a Forward Flight
Authors: S. M. Dash, K. B. Lua, T. T. Lim
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This paper presents results of numerical and experimental studies on a two-dimensional (2D) flapping elliptic airfoil in a forward flight condition at Reynolds number of 5000. The study is motivated from an earlier investigation which shows that the deterioration in thrust performance of a sinusoidal heaving and pitching 2D (NACA0012) airfoil at high flapping frequency can be recovered by changing the effective angle of attack profile to square wave, sawtooth, or cosine wave shape. To better understand why such modifications lead to superior thrust performance, we take a closer look at the transient aerodynamic force behavior of an airfoil when the effective angle of attack profile changes gradually from a generic smooth trapezoidal profile to a sinusoid shape by modifying the base length of the trapezoid. The choice of using a smooth trapezoidal profile is to avoid the infinite acceleration condition encountered in the square wave profile. Our results show that the enhancement in the time-averaged thrust performance at high flapping frequency can be attributed to the delay and reduction in the drag producing valley region in the transient thrust force coefficient when the effective angle of attack profile changes from sinusoidal to trapezoidal.Keywords: Two-dimensional Flapping Airfoil, Thrust Performance, Effective Angle of Attack, CFD and Experiments.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18154372 The Proof of Two Conjectures Related to Pell-s Equation x2 −Dy2 = ± 4
Authors: Armend Sh. Shabani
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Let D ≠ 1 be a positive non-square integer. In this paper are given the proofs for two conjectures related to Pell-s equation x2 -Dy2 = ± 4, proposed by A. Tekcan.Keywords: Pell's equation, solutions of Pell's equation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12374371 Unsteady Natural Convection in a Square Cavity Partially Filled with Porous Media Using a Thermal Non-Equilibrium Model
Authors: Ammar Alsabery, Habibis Saleh, Norazam Arbin, Ishak Hashim
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Unsteady natural convection and heat transfer in a square cavity partially filled with porous media using a thermal non-equilibrium model is studied in this paper. The left vertical wall is maintained at a constant hot temperature Th and the right vertical wall is maintained at a constant cold temperature Tc, while the horizontal walls are adiabatic. The governing equations are obtained by applying the Darcy model and Boussinesq approximation. COMSOL’s finite element method is used to solve the non-dimensional governing equations together with specified boundary conditions. The governing parameters of this study are the Rayleigh number (Ra = 10^5, and Ra = 10^6 ), Darcy namber (Da = 10^−2, and Da = 10^−3), the modified thermal conductivity ratio (10^−1 ≤ γ ≤ 10^4), the inter-phase heat transfer coefficien (10^−1 ≤ H ≤ 10^3) and the time dependent (0.001 ≤ τ ≤ 0.2). The results presented for values of the governing parameters in terms of streamlines in both fluid/porous-layer, isotherms of fluid in fluid/porous-layer, isotherms of solid in porous layer, and average Nusselt number.
Keywords: Unsteady natural convection, Thermal non-equilibrium model, Darcy model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27534370 A New Recognition Scheme for Machine- Printed Arabic Texts based on Neural Networks
Authors: Z. Shaaban
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This paper presents a new approach to tackle the problem of recognizing machine-printed Arabic texts. Because of the difficulty of recognizing cursive Arabic words, the text has to be normalized and segmented to be ready for the recognition stage. The new scheme for recognizing Arabic characters depends on multiple parallel neural networks classifier. The classifier has two phases. The first phase categories the input character into one of eight groups. The second phase classifies the character into one of the Arabic character classes in the group. The system achieved high recognition rate.
Keywords: Neural Networks, character recognition, feature extraction, multiple networks, Arabic text.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14774369 Model-Driven and Data-Driven Approaches for Crop Yield Prediction: Analysis and Comparison
Authors: Xiangtuo Chen, Paul-Henry Cournéde
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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.Keywords: Crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11744368 Phenomenological and Semi-microscopic Analysis for Elastic Scattering of Protons on 6,7Li
Authors: A. Amar, N. Burtebayev, Sh. Hamada, Kerimkulov Zhambul, N. Amangieldy
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Analysis of the elastic scattering of protons on 6,7Li nuclei has been done in the framework of the optical model at the beam energies up to 50 MeV. Differential cross sections for the 6,7Li + p scattering were measured over the proton laboratory–energy range from 400 to 1050 keV. The elastic scattering of 6,7Li+p data at different proton incident energies have been analyzed using singlefolding model. In each case the real potential obtained from the folding model was supplemented by a phenomenological imaginary potential, and during the fitting process the real potential was normalized and the imaginary potential optimized. Normalization factor NR is calculated in the range between 0.70 and 0.84.Keywords: scattering of protons on 6, 7Li nuclei, Esis88 Codesingle-folding model, phenomenological.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13754367 Novel Adaptive Channel Equalization Algorithms by Statistical Sampling
Authors: János Levendovszky, András Oláh
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In this paper, novel statistical sampling based equalization techniques and CNN based detection are proposed to increase the spectral efficiency of multiuser communication systems over fading channels. Multiuser communication combined with selective fading can result in interferences which severely deteriorate the quality of service in wireless data transmission (e.g. CDMA in mobile communication). The paper introduces new equalization methods to combat interferences by minimizing the Bit Error Rate (BER) as a function of the equalizer coefficients. This provides higher performance than the traditional Minimum Mean Square Error equalization. Since the calculation of BER as a function of the equalizer coefficients is of exponential complexity, statistical sampling methods are proposed to approximate the gradient which yields fast equalization and superior performance to the traditional algorithms. Efficient estimation of the gradient is achieved by using stratified sampling and the Li-Silvester bounds. A simple mechanism is derived to identify the dominant samples in real-time, for the sake of efficient estimation. The equalizer weights are adapted recursively by minimizing the estimated BER. The near-optimal performance of the new algorithms is also demonstrated by extensive simulations. The paper has also developed a (Cellular Neural Network) CNN based approach to detection. In this case fast quadratic optimization has been carried out by t, whereas the task of equalizer is to ensure the required template structure (sparseness) for the CNN. The performance of the method has also been analyzed by simulations.
Keywords: Cellular Neural Network, channel equalization, communication over fading channels, multiuser communication, spectral efficiency, statistical sampling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15204366 Sensitive Analysis of the ZF Model for ABC Multi Criteria Inventory Classification
Authors: Makram Ben Jeddou
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ABC classification is widely used by managers for inventory control. The classical ABC classification is based on Pareto principle and according to the criterion of the annual use value only. Single criterion classification is often insufficient for a closely inventory control. Multi-criteria inventory classification models have been proposed by researchers in order to consider other important criteria. From these models, we will consider a specific model in order to make a sensitive analysis on the composite score calculated for each item. In fact, this score, based on a normalized average between a good and a bad optimized index, can affect the ABC-item classification. We will focus on items differently assigned to classes and then propose a classification compromise.Keywords: ABC classification, Multi criteria inventory classification models, ZF-model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25174365 Effect of Zr Addition on Mechanical Properties of Cr-Mo Plastic Mold Steels
Authors: Hyun-Ho Kim, Seok-Jae Lee, Oh-Yeon Lee
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We investigated the effects of the additions of Zr and other alloying elements on the mechanical properties and microstructure in Cr-Mo plastic mold steels. The addition of alloying elements changed the microstructure of the normalized samples from the upper bainite to lower bainite due to the increased hardenability. The tempering temperature influenced the strength and hardness values, especially the phenomenon of 350oC embrittlement was observed. The alloy additions of Cr, Mo, and V improved the resistance to the temper embrittlement. The addition of Zr improved the tensile strength and yield strength, but the impact energy was sharply decreased. It may be caused by the formation of Zr-MnS inclusion and rectangular-shaped Zr inclusion due to the Zr addition.
Keywords: Inclusions, mechanical properties, plastic mold steel, Zr addition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23304364 Parallel Multisplitting Methods for Singular Linear Systems
Authors: Guangbin Wang, Fuping Tan
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In this paper, we discuss convergence of the extrapolated iterative methods for linear systems with the coefficient matrices are singular H-matrices. And we present the sufficient and necessary conditions for convergence of the extrapolated iterative methods. Moreover, we apply the results to the GMAOR methods. Finally, we give one numerical example.
Keywords: Singular H-matrix, linear systems, extrapolated iterative method, GMAOR method, convergence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13514363 Vortex-Shedding Suppression in Mixed Convective Flow past a Heated Square Cylinder
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The present study investigates numerically the phenomenon of vortex-shedding and its suppression in twodimensional mixed convective flow past a square cylinder under the joint influence of buoyancy and free-stream orientation with respect to gravity. The numerical experiments have been conducted at a fixed Reynolds number (Re) of 100 and Prandtl number (Pr) of 0.71, while Richardson number (Ri) is varied from 0 to 1.6 and freestream orientation, α, is kept in the range 0o≤ α ≤ 90o, with 0o corresponding to an upward flow and 90o representing a cross-flow scenario, respectively. The continuity, momentum and energy equations, subject to Boussinesq approximation, are discretized using a finite difference method and are solved by a semi-explicit pressure correction scheme. The critical Richardson number, leading to the suppression of the vortex-shedding (Ric), is estimated by using Stuart-Landau theory at various free-stream orientations and the neutral curve is obtained in the Ri-α plane. The neutral curve exhibits an interesting non-monotonic behavior with Ric first increasing with increasing values of α upto 45o and then decreasing till 70o. Beyond 70o, the neutral curve again exhibits a sharp increasing asymptotic trend with Ric approaching very large values as α approaches 90o. The suppression of vortex shedding is not observed at α = 90o (cross-flow). In the unsteady flow regime, the Strouhal number (St) increases with the increase in Richardson number.Keywords: bluff body, buoyancy, free-stream orientation, vortex-shedding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22714362 Routing Load Analysis over 802.11 DCF of Reactive Routing Protocols DSR and DYMO
Authors: Parma Nand, S.C. Sharma
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The Mobile Ad-hoc Network (MANET) is a collection of self-configuring and rapidly deployed mobile nodes (routers) without any central infrastructure. Routing is one of the potential issues. Many routing protocols are reported but it is difficult to decide which one is best in all scenarios. In this paper on demand routing protocols DSR and DYMO based on IEEE 802.11 DCF MAC protocol are examined and characteristic summary of these routing protocols is presented. Their performance is analyzed and compared on performance measuring metrics throughput, dropped packets due to non availability of routes, duplicate RREQ generated for route discovery and normalized routing load by varying CBR data traffic load using QualNet 5.0.2 network simulator.
Keywords: Adhoc networks, wireless networks, CBR, routingprotocols, route discovery, simulation, performance evaluation, MAC, IEEE 802.11.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17244361 Optimal Combination for Modal Pushover Analysis by Using Genetic Algorithm
Authors: K. Shakeri, M. Mohebbi
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In order to consider the effects of the higher modes in the pushover analysis, during the recent years several multi-modal pushover procedures have been presented. In these methods the response of the considered modes are combined by the square-rootof- sum-of-squares (SRSS) rule while application of the elastic modal combination rules in the inelastic phases is no longer valid. In this research the feasibility of defining an efficient alternative combination method is investigated. Two steel moment-frame buildings denoted SAC-9 and SAC-20 under ten earthquake records are considered. The nonlinear responses of the structures are estimated by the directed algebraic combination of the weighted responses of the separate modes. The weight of the each mode is defined so that the resulted response of the combination has a minimum error to the nonlinear time history analysis. The genetic algorithm (GA) is used to minimize the error and optimize the weight factors. The obtained optimal factors for each mode in different cases are compared together to find unique appropriate weight factors for each mode in all cases.Keywords: Genetic Algorithm, Modal Pushover, Optimalweight.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18044360 Concurrent Testing of ADC for Embedded System
Authors: Y.B.Gandole
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Compaction testing methods allow at-speed detecting of errors while possessing low cost of implementation. Owing to this distinctive feature, compaction methods have been widely used for built-in testing, as well as external testing. In the latter case, the bandwidth requirements to the automated test equipment employed are relaxed which reduces the overall cost of testing. Concurrent compaction testing methods use operational signals to detect misbehavior of the device under test and do not require input test stimuli. These methods have been employed for digital systems only. In the present work, we extend the use of compaction methods for concurrent testing of analog-to-digital converters. We estimate tolerance bounds for the result of compaction and evaluate the aliasing rate.Keywords: Analog-to Digital Converter, Embedded system, Concurrent Testing
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16134359 Influences of Juice Extraction and Drying Methods on the Chemical Analysis of Lemon Peels
Authors: Azza A. Abou-Arab, Marwa H. Mahmoud, Ferial M. Abu-Salem
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This study aimed to determine the influence of some different juice extraction methods (screw type hand operated juice extractor and pressed squeeze juice extractor) as well as drying methods (microwave, solar and oven drying) on the chemical properties of lemon peels. It could be concluded that extraction of juice by screw type and drying of peel using the microwave drying method were the best preparative processing steps methods for lemon peel utilization as food additives.
Keywords: Lemon peel, extraction of juice methods, chemical analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10264358 A Survey of Business Component Identification Methods and Related Techniques
Authors: Zhongjie Wang, Xiaofei Xu, Dechen Zhan
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With deep development of software reuse, componentrelated technologies have been widely applied in the development of large-scale complex applications. Component identification (CI) is one of the primary research problems in software reuse, by analyzing domain business models to get a set of business components with high reuse value and good reuse performance to support effective reuse. Based on the concept and classification of CI, its technical stack is briefly discussed from four views, i.e., form of input business models, identification goals, identification strategies, and identification process. Then various CI methods presented in literatures are classified into four types, i.e., domain analysis based methods, cohesion-coupling based clustering methods, CRUD matrix based methods, and other methods, with the comparisons between these methods for their advantages and disadvantages. Additionally, some insufficiencies of study on CI are discussed, and the causes are explained subsequently. Finally, it is concluded with some significantly promising tendency about research on this problem.Keywords: Business component, component granularity, component identification, reuse performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19744357 A Comparison of First and Second Order Training Algorithms for Artificial Neural Networks
Authors: Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C. Ardil
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Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton?s methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.Keywords: Backpropagation algorithm, conjugacy condition, line search, matrix perturbation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36434356 Dynamic Voltage Stability Estimation using Particle Filter
Authors: Osea Zebua, Norikazu Ikoma, Hiroshi Maeda
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Estimation of voltage stability based on optimal filtering method is presented. PV curve is used as a tool for voltage stability analysis. Dynamic voltage stability estimation is done by using particle filter method. Optimum value (nose point) of PV curve can be estimated by estimating parameter of PV curve equation optimal value represents critical voltage and condition at specified point of measurement. Voltage stability is then estimated by analyzing loading margin condition c stimating equation. This maximum loading ecified dynamically.Keywords: normalized PV curve, optimal filtering method particle filter, voltage stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18014355 Theoretical Analysis of the Effect of Accounting for Special Methods in Similarity-Based Cohesion Measurement
Authors: Jehad Al Dallal
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Class cohesion is an important object-oriented software quality attributes, and it refers to the degree of relatedness of class attributes and methods. Several class cohesion measures are proposed in the literature, and the impact of considering the special methods (i.e., constructors, destructors, and access and delegation methods) in cohesion calculation is not thoroughly theoretically studied for most of them. In this paper, we address this issue for three popular similarity-based class cohesion measures. For each of the considered measures we theoretically study the impact of including or excluding special methods on the values that are obtained by applying the measure. This study is based on analyzing the definitions and formulas that are proposed for the measures. The results show that including/excluding special methods has a considerable effect on the obtained cohesion values and that this effect varies from one measure to another. The study shows the importance of considering the types of methods that have to be accounted for when proposing a similarity-based cohesion measure.
Keywords: Object-oriented class, software quality, class cohesion measure, class cohesion, special methods.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16704354 Smart Spoiler for Race Car
Authors: M.H. Djavareshkian, A. Esmaeli
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A pressure-based implicit procedure to solve Navier- Stokes equations on a nonorthogonal mesh with collocated finite volume formulation is used to simulate flow around the smart and conventional flaps of spoiler under the ground effect. Cantilever beam with uniformly varying load with roller support at the free end is considered for smart flaps. The boundedness criteria for this procedure are determined from a Normalized Variable diagram (NVD) scheme. The procedure incorporates es the k -ε eddyviscosity turbulence model. The method is first validated against experimental data. Then, the algorithm is applied for turbulent aerodynamic flows around a spoiler section with smart and conventional flaps for different attack angle, flap angle and ground clearance where the results of two flaps are compared.Keywords: Smart spoiler, Ground Effect, Flap, Aerodynamic coefficients, Race car.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25194353 Localized Meshfree Methods for Solving 3D-Helmholtz Equation
Authors: Reza Mollapourasl, Majid Haghi
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In this study, we develop local meshfree methods known as radial basis function-generated finite difference (RBF-FD) method and Hermite finite difference (RBF-HFD) method to design stencil weights and spatial discretization for Helmholtz equation. The convergence and stability of schemes are investigated numerically in three dimensions with irregular shaped domain. These localized meshless methods incorporate the advantages of the RBF method, finite difference and Hermite finite difference methods to handle the ill-conditioning issue that often destroys the convergence rate of global RBF methods. Moreover, numerical illustrations show that the proposed localized RBF type methods are efficient and applicable for problems with complex geometries. The convergence and accuracy of both schemes are compared by solving a test problem.
Keywords: Radial basis functions, Hermite finite difference, Helmholtz equation, stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1294352 Using the OWA Operator in the Minkowski Distance
Authors: José M. Merigó, Anna M. Gil-Lafuente
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We study different types of aggregation operators such as the ordered weighted averaging (OWA) operator and the generalized OWA (GOWA) operator. We analyze the use of OWA operators in the Minkowski distance. We will call these new distance aggregation operator the Minkowski ordered weighted averaging distance (MOWAD) operator. We give a general overview of this type of generalization and study some of their main properties. We also analyze a wide range of particular cases found in this generalization such as the ordered weighted averaging distance (OWAD) operator, the Euclidean ordered weighted averaging distance (EOWAD) operator, the normalized Minkowski distance, etc. Finally, we give an illustrative example of the new approach where we can see the different results obtained by using different aggregation operators.Keywords: Aggregation operators, Minkowski distance, OWA operators, Selection of strategies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21014351 On the Integer Solutions of the Pell Equation x2 - dy2 = 2t
Authors: Ahmet Tekcan, Betül Gezer, Osman Bizim
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Let k ≥ 1 and t ≥ 0 be two integers and let d = k2 + k be a positive non-square integer. In this paper, we consider the integer solutions of Pell equation x2 - dy2 = 2t. Further we derive a recurrence relation on the solutions of this equation.
Keywords: Pell equation, Diophantine equation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23874350 Methods for Preparation of Soil Samples for Determination of Trace Elements
Authors: S. Krustev, V. Angelova, K. Ivanov, P. Zaprjanova
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It is generally accepted that only about ten microelements are vitally important to all plants, and approximately ten more elements are proved to be significant for the development of some species. The main methods for their determination in soils are the atomic spectral techniques - AAS and ICP-OAS. Critical stage to obtain correct results for content of heavy metals and nutrients in the soil is the process of mineralization. A comparative study of the most widely spread methods for soil sample preparation for determination of some trace elements was carried out. Three most commonly used methods for sample preparation were used as follows: ISO11466, EPA Method 3051 and BDS ISO 14869-1. Their capabilities were assessed and their bounds of applicability in determining the levels of the most important microelements in agriculture were defined.
Keywords: Comparative study, mineralization methods, trace elements.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1241