Search results for: adaptivemethod with reference model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7905

Search results for: adaptivemethod with reference model

7575 SiC Merged PiN and Schottky (MPS) Power Diodes Electrothermal Modeling in SPICE

Authors: A. Lakrim, D. Tahri

Abstract:

This paper sets out a behavioral macro-model of a Merged PiN and Schottky (MPS) diode based on silicon carbide (SiC). This model holds good for both static and dynamic electrothermal simulations for industrial applications. Its parameters have been worked out from datasheets curves by drawing on the optimization method: Simulated Annealing (SA) for the SiC MPS diodes made available in the industry. The model also adopts the Analog Behavioral Model (ABM) of PSPICE in which it has been implemented. The thermal behavior of the devices was also taken into consideration by making use of Foster’ canonical network as figured out from electro-thermal measurement provided by the manufacturer of the device.

Keywords: SiC MPS Diode, electro-thermal, SPICE Model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1916
7574 Mapping Crime against Women in India: Spatio-Temporal Analysis, 2001-2012

Authors: Ritvik Chauhan, Vijay Kumar Baraik

Abstract:

Women are most vulnerable to crime despite occupying central position in shaping a society as the first teacher of children. In India too, having equal rights and constitutional safeguards, the incidences of crime against them are large and grave. In this context of crime against women, especially rape has been increasing over time. This paper explores the spatial and temporal aspects of crime against women in India with special reference to rape. It also examines the crime against women with its spatial, socio-economic and demographic associates using related data obtained from the National Crime Records Bureau India, Indian Census and other government sources of the Government of India. The simple statistical, choropleth mapping and other cartographic representation methods have been used to see the crime rates, spatio-temporal patterns of crime, and association of crime with its correlates.  The major findings are visible spatial variations across the country and are also in the rising trends in terms of incidence and rates over the reference period. The study also indicates that the geographical associations are somewhat observed. However, selected indicators of socio-economic factors seem to have no significant bearing on crime against women at this level.

Keywords: Crime against women, crime mapping, trend analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1653
7573 Parametric Study of Vertical Diffusion Still for Water Desalination

Authors: A. Seleem, M. Mortada, M. El Morsi, M. Younan

Abstract:

Diffusion stills have been effective in water desalination. The present work represents a model of the distillation process by using vertical single-effect diffusion stills. A semianalytical model has been developed to model the process. A software computer code using Engineering Equation Solver EES software has been developed to solve the equations of the developed model. An experimental setup has been constructed, and used for the validation of the model. The model is also validated against former literature results. The results obtained from the present experimental test rig, and the data from the literature, have been compared with the results of the code to find its best range of validity. In addition, a parametric analysis of the system has been developed using the model to determine the effect of operating conditions on the system's performance. The dominant parameters that affect the productivity of the still are the hot plate temperature that ranges from (55- 90°C) and feed flow rate in range of (0.00694-0.0211 kg/m2-s).

Keywords: Analytical Model, Solar Distillation, Sustainable Water Systems, Vertical Diffusion Still.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2370
7572 A Numerical Model for Studying Convectional Lifting Processes in the Tropics

Authors: Chantawan Noisri, Robert Harold Buchanan Exell

Abstract:

A simple model for studying convectional lifting processes in the tropics is described in this paper with some tests of the model in dry air. The model consists of the density equation, the wind equation, the vertical velocity equation, and the temperature equation. The model domain is two-dimensional with length 100 km and height 17.5 km. Plan for experiments to investigate the effects of the heating surface, the deep convection approximation and the treatment of velocities at the boundaries are discussed. Equations for the simplified treatment of moisture in the atmosphere in future numerical experiments are also given.

Keywords: Numerical weather prediction, Finite differences, Convection lifting.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1255
7571 Validity Domains of Beams Behavioural Models: Efficiency and Reduction with Artificial Neural Networks

Authors: Keny Ordaz-Hernandez, Xavier Fischer, Fouad Bennis

Abstract:

In a particular case of behavioural model reduction by ANNs, a validity domain shortening has been found. In mechanics, as in other domains, the notion of validity domain allows the engineer to choose a valid model for a particular analysis or simulation. In the study of mechanical behaviour for a cantilever beam (using linear and non-linear models), Multi-Layer Perceptron (MLP) Backpropagation (BP) networks have been applied as model reduction technique. This reduced model is constructed to be more efficient than the non-reduced model. Within a less extended domain, the ANN reduced model estimates correctly the non-linear response, with a lower computational cost. It has been found that the neural network model is not able to approximate the linear behaviour while it does approximate the non-linear behaviour very well. The details of the case are provided with an example of the cantilever beam behaviour modelling.

Keywords: artificial neural network, validity domain, cantileverbeam, non-linear behaviour, model reduction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1401
7570 Dynamic Simulation of IC Engine Bearings for Fault Detection and Wear Prediction

Authors: M. D. Haneef, R. B. Randall, Z. Peng

Abstract:

Journal bearings used in IC engines are prone to premature failures and are likely to fail earlier than the rated life due to highly impulsive and unstable operating conditions and frequent starts/stops. Vibration signature extraction and wear debris analysis techniques are prevalent in industry for condition monitoring of rotary machinery. However, both techniques involve a great deal of technical expertise, time, and cost. Limited literature is available on the application of these techniques for fault detection in reciprocating machinery, due to the complex nature of impact forces that confounds the extraction of fault signals for vibration-based analysis and wear prediction. In present study, a simulation model was developed to investigate the bearing wear behaviour, resulting because of different operating conditions, to complement the vibration analysis. In current simulation, the dynamics of the engine was established first, based on which the hydrodynamic journal bearing forces were evaluated by numerical solution of the Reynold’s equation. In addition, the essential outputs of interest in this study, critical to determine wear rates are the tangential velocity and oil film thickness between the journals and bearing sleeve, which if not maintained appropriately, have a detrimental effect on the bearing performance. Archard’s wear prediction model was used in the simulation to calculate the wear rate of bearings with specific location information as all determinative parameters were obtained with reference to crank rotation. Oil film thickness obtained from the model was used as a criterion to determine if the lubrication is sufficient to prevent contact between the journal and bearing thus causing accelerated wear. A limiting value of 1 μm was used as the minimum oil film thickness needed to prevent contact. The increased wear rate with growing severity of operating conditions is analogous and comparable to the rise in amplitude of the squared envelope of the referenced vibration signals. Thus on one hand, the developed model demonstrated its capability to explain wear behaviour and on the other hand it also helps to establish a co-relation between wear based and vibration based analysis. Therefore, the model provides a cost effective and quick approach to predict the impending wear in IC engine bearings under various operating conditions.

Keywords: Condition monitoring, IC engine, journal bearings, vibration analysis, wear prediction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2245
7569 Model of Appropriate Science Teaching for Mathayomsuksa 3 (Grade 9) in Ang-Thong Province

Authors: Lertlop, W

Abstract:

This research aims to study the appropriate model of Science teaching for students, academic achievement and to survey students- attitudes toward using appropriate for students in Mathayomsuksa 3 in Ang-Thong province. The research results were as follows: 1. The appropriate model of Science teaching for Mathayomsuksa 3 students in Ang-Thong province including these following five steps: Step 1. The introduction of the lessons. Step 2. Setting the hypothesis. Step 3. Doing the experiment /survey. Step 4. Making conclusion. Step 5. Applying to daily life or other subjects. 2. There is no significant difference between using appropriate model teaching and regular teaching at 0.05 level significant difference. 3. There is a significant difference between before and after teaching using appropriate model of Science teaching at 0.05 level. 4. The satisfaction of students- attitudes to using the appropriate model of Science teaching for students was in intermediate level.

Keywords: Pedagogy, science teaching model, Ang-Thong province.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1828
7568 Application of Biometrics to Obtain High Entropy Cryptographic Keys

Authors: Sanjay Kanade, Danielle Camara, Dijana Petrovska-Delacretaz, Bernadette Dorizzi

Abstract:

In this paper, a two factor scheme is proposed to generate cryptographic keys directly from biometric data, which unlike passwords, are strongly bound to the user. Hash value of the reference iris code is used as a cryptographic key and its length depends only on the hash function, being independent of any other parameter. The entropy of such keys is 94 bits, which is much higher than any other comparable system. The most important and distinct feature of this scheme is that it regenerates the reference iris code by providing a genuine iris sample and the correct user password. Since iris codes obtained from two images of the same eye are not exactly the same, error correcting codes (Hadamard code and Reed-Solomon code) are used to deal with the variability. The scheme proposed here can be used to provide keys for a cryptographic system and/or for user authentication. The performance of this system is evaluated on two publicly available databases for iris biometrics namely CBS and ICE databases. The operating point of the system (values of False Acceptance Rate (FAR) and False Rejection Rate (FRR)) can be set by properly selecting the error correction capacity (ts) of the Reed- Solomon codes, e.g., on the ICE database, at ts = 15, FAR is 0.096% and FRR is 0.76%.

Keywords:

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2057
7567 Knowledge Management Model for Research Projects Masters Program

Authors: Víctor Hugo Medina García, Darío Alejandro Segura Torres

Abstract:

This paper presents the adaptation of the knowledge management model and intellectual capital measurement NOVA to the needs of work or research project must be developed when conducting a program of graduate-level master. Brackets are added in each of the blocks which is represented in the original model NOVA and which allows to represent those involved in each of these.

Keywords: Knowledge management, masters programs, Nova model, research projects

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1304
7566 Toward a Risk Assessment Model Based On Multi-Agent System for Cloud Consumer

Authors: Saadia Drissi, Siham Benhadou, Hicham Medromi

Abstract:

The cloud computing is an innovative paradigm that introduces several changes in technology that have resulted a new ways for cloud providers to deliver their services to cloud consumers mainly in term of security risk assessment, thus, adapting a current risk assessment tools to cloud computing is a very difficult task due to its several characteristics that challenge the effectiveness of risk assessment approaches. As consequence, there is a need of risk assessment model adapted to cloud computing. This paper requires a new risk assessment model based on multi-agent system and AHP model as fundamental steps towards the development of flexible risk assessment approach regarding cloud consumers.

Keywords: Cloud computing, risk assessment model, multi-agent system, AHP model, cloud consumer.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2214
7565 2D and 3D Unsteady Simulation of the Heat Transfer in the Sample during Heat Treatment by Moving Heat Source

Authors: Z. Veselý, M. Honner, J. Mach

Abstract:

The aim of the performed work is to establish the 2D and 3D model of direct unsteady task of sample heat treatment by moving source employing computer model on the basis of finite element method. Complex boundary condition on heat loaded sample surface is the essential feature of the task. Computer model describes heat treatment of the sample during heat source movement over the sample surface. It is started from 2D task of sample cross section as a basic model. Possibilities of extension from 2D to 3D task are discussed. The effect of the addition of third model dimension on temperature distribution in the sample is showed. Comparison of various model parameters on the sample temperatures is observed. Influence of heat source motion on the depth of material heat treatment is shown for several velocities of the movement. Presented computer model is prepared for the utilization in laser treatment of machine parts.

Keywords: Computer simulation, unsteady model, heat treatment, complex boundary condition, moving heat source.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2002
7564 Fuzzy Controller Design for TCSC to Improve Power Oscillations Damping

Authors: M Nayeripour, H. Khorsand, A. Roosta, T. Niknam, E. Azad

Abstract:

Series compensators have been used for many years, to increase the stability and load ability of transmission line. They compensate retarded or advanced volt drop of transmission lines by placing advanced or retarded voltage in series with them to compensate the effective reactance, which cause to increase load ability of transmission lines. In this paper, two method of fuzzy controller, based on power reference tracking and impedance reference tracking have been developed on TCSC controller in order to increase load ability and improving power oscillation damping of system. In these methods, fire angle of thyristors are determined directly through the special Rule-bases with the error and change of error as the inputs. The simulation results of two area four- machines power system show the good performance of power oscillation damping in system. Comparison of this method with classical PI controller shows the increasing speed of system response in power oscillation damping.

Keywords: TCSC, Two area network, Fuzzy controller, Power oscillation damping.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1964
7563 Adaptive Gaussian Mixture Model for Skin Color Segmentation

Authors: Reza Hassanpour, Asadollah Shahbahrami, Stephan Wong

Abstract:

Skin color based tracking techniques often assume a static skin color model obtained either from an offline set of library images or the first few frames of a video stream. These models can show a weak performance in presence of changing lighting or imaging conditions. We propose an adaptive skin color model based on the Gaussian mixture model to handle the changing conditions. Initial estimation of the number and weights of skin color clusters are obtained using a modified form of the general Expectation maximization algorithm, The model adapts to changes in imaging conditions and refines the model parameters dynamically using spatial and temporal constraints. Experimental results show that the method can be used in effectively tracking of hand and face regions.

Keywords: Face detection, Segmentation, Tracking, Gaussian Mixture Model, Adaptation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2384
7562 External Effects on Dynamic Competitive Model of Domestic Airline and High Speed Rail

Authors: Shih-Ching Lo, Yu-Ping Liao

Abstract:

Social-economic variables influence transportation demand largely. Analyses of discrete choice model consider social-economic variables to study traveler-s mode choice and demand. However, to calibrate the discrete choice model needs to have plenty of questionnaire survey. Also, an aggregative model is proposed. The historical data of passenger volumes for high speed rail and domestic civil aviation are employed to calibrate and validate the model. In this study, models with different social-economic variables, which are oil price, GDP per capita, CPI and economic growth rate, are compared. From the results, the model with the oil price is better than models with the other social-economic variables.

Keywords: forecasting, passenger volume, dynamic competitive model, social-economic variables, oil price.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1549
7561 A Comparison of Air Pollution in Developed and Developing Cities: A Case Study of London and Beijing

Authors: S. X. Sun, Q. Wang

Abstract:

With the rapid development of industrialization, countries in different stages of development in the world have gradually begun to pay attention to the impact of air pollution on health and the environment. Air control in developed countries is an effective reference for air control in developing countries. Artificial intelligence and other technologies also play a positive role in the prediction of air pollution. By comparing the annual changes of pollution in London and Beijing, this paper concludes that the pollution in developed cities is relatively low and stable, while the pollution in Beijing is relatively heavy and unstable, but is clearly improving. In addition, by analyzing the changes of major pollutants in Beijing in the past eight years, it is concluded that all pollutants except O3 show a significant downward trend. In addition, all pollutants except O3 have certain correlation. For example, PM10 and PM2.5 have the greatest influence on air quality index (AQI). Python, which is commonly used by artificial intelligence, is used as the main software to establish two models, support vector machine (SVM) and linear regression. By comparing the two models under the same conditions, it is concluded that SVM has higher accuracy in pollution prediction. The results of this study provide valuable reference for pollution control and prediction in developing countries.

Keywords: Air pollution, particulate matter, AQI, correlation coefficient, air pollution prediction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 506
7560 Javanese Character Recognition Using Hidden Markov Model

Authors: Anastasia Rita Widiarti, Phalita Nari Wastu

Abstract:

Hidden Markov Model (HMM) is a stochastic method which has been used in various signal processing and character recognition. This study proposes to use HMM to recognize Javanese characters from a number of different handwritings, whereby HMM is used to optimize the number of state and feature extraction. An 85.7 % accuracy is obtained as the best result in 16-stated vertical model using pure HMM. This initial result is satisfactory for prompting further research.

Keywords: Character recognition, off-line handwritingrecognition, Hidden Markov Model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1949
7559 Analytical Model to Predict the Shear Capacity of Reinforced Concrete Beams Externally Strengthened with CFRP Composites Conditions

Authors: Rajai Al-Rousan

Abstract:

This paper presents a proposed analytical model for predicting the shear strength of reinforced concrete beams strengthened with CFRP composites as external reinforcement. The proposed analytical model can predict the shear contribution of CFRP composites of RC beams with an acceptable coefficient of correlation with the tested results. Based on the comparison of the proposed model with the published well-known models (ACI model, Triantafillou model, and Colotti model), the ACI model had a wider range of 0.16 to 10.08 for the ratio between tested and predicted ultimate shears at failure. Also, an acceptable range of 0.27 to 2.78 for the ratio between tested and predicted ultimate shears by the Triantafillou model. Finally, the best prediction (the ratio between the tested and predicted ones) of the ultimate shear capacity is observed by using Colotti model with a range of 0.20 to 1.78. Thus, the contribution of the CFRP composites as external reinforcement can be predicted with high accuracy by using the proposed analytical model.

Keywords: Predicting, shear capacity, reinforced concrete, beams, strengthened, externally, CFRP composites.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 837
7558 An Enhanced Artificial Neural Network for Air Temperature Prediction

Authors: Brian A. Smith, Ronald W. McClendon, Gerrit Hoogenboom

Abstract:

The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. An improved model for temperature prediction in Georgia was developed by including information on seasonality and modifying parameters of an existing artificial neural network model. Alternative models were compared by instantiating and training multiple networks for each model. The inclusion of up to 24 hours of prior weather information and inputs reflecting the day of year were among improvements that reduced average four-hour prediction error by 0.18°C compared to the prior model. Results strongly suggest model developers should instantiate and train multiple networks with different initial weights to establish appropriate model parameters.

Keywords: Time-series forecasting, weather modeling.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1821
7557 Discovering the Dimension of Abstractness: Structure-Based Model that Learns New Categories and Categorizes on Different Levels of Abstraction

Authors: Georgi I. Petkov, Ivan I. Vankov, Yolina A. Petrova

Abstract:

A structure-based model of category learning and categorization at different levels of abstraction is presented. The model compares different structures and expresses their similarity implicitly in the forms of mappings. Based on this similarity, the model can categorize different targets either as members of categories that it already has or creates new categories. The model is novel using two threshold parameters to evaluate the structural correspondence. If the similarity between two structures exceeds the higher threshold, a new sub-ordinate category is created. Vice versa, if the similarity does not exceed the higher threshold but does the lower one, the model creates a new category on higher level of abstraction.

Keywords: Analogy-making, categorization, learning of categories, abstraction, hierarchical structure.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 745
7556 A Mean–Variance–Skewness Portfolio Optimization Model

Authors: Kostas Metaxiotis

Abstract:

Portfolio optimization is one of the most important topics in finance. This paper proposes a mean–variance–skewness (MVS) portfolio optimization model. Traditionally, the portfolio optimization problem is solved by using the mean–variance (MV) framework. In this study, we formulate the proposed model as a three-objective optimization problem, where the portfolio's expected return and skewness are maximized whereas the portfolio risk is minimized. For solving the proposed three-objective portfolio optimization model we apply an adapted version of the non-dominated sorting genetic algorithm (NSGAII). Finally, we use a real dataset from FTSE-100 for validating the proposed model.

Keywords: Evolutionary algorithms, portfolio optimization, skewness, stock selection.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1343
7555 The Gasoil Hydrofining Kinetics Constants Identification

Authors: C. Patrascioiu, V. Matei, N. Nicolae

Abstract:

The paper describes the experiments and the kinetic parameters calculus of the gasoil hydrofining. They are presented experimental results of gasoil hidrofining using Mo and promoted with Ni on aluminum support catalyst. The authors have adapted a kinetic model gasoil hydrofining. Using this proposed kinetic model and the experimental data they have calculated the parameters of the model. The numerical calculus is based on minimizing the difference between the experimental sulf concentration and kinetic model estimation.

Keywords: Hydrofining, kinetic, modeling, optimization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1979
7554 Feature Extraction Technique for Prediction the Antigenic Variants of the Influenza Virus

Authors: Majid Forghani, Michael Khachay

Abstract:

In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.

Keywords: Antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 738
7553 Implementing an Intuitive Reasoner with a Large Weather Database

Authors: Yung-Chien Sun, O. Grant Clark

Abstract:

In this paper, the implementation of a rule-based intuitive reasoner is presented. The implementation included two parts: the rule induction module and the intuitive reasoner. A large weather database was acquired as the data source. Twelve weather variables from those data were chosen as the “target variables" whose values were predicted by the intuitive reasoner. A “complex" situation was simulated by making only subsets of the data available to the rule induction module. As a result, the rules induced were based on incomplete information with variable levels of certainty. The certainty level was modeled by a metric called "Strength of Belief", which was assigned to each rule or datum as ancillary information about the confidence in its accuracy. Two techniques were employed to induce rules from the data subsets: decision tree and multi-polynomial regression, respectively for the discrete and the continuous type of target variables. The intuitive reasoner was tested for its ability to use the induced rules to predict the classes of the discrete target variables and the values of the continuous target variables. The intuitive reasoner implemented two types of reasoning: fast and broad where, by analogy to human thought, the former corresponds to fast decision making and the latter to deeper contemplation. . For reference, a weather data analysis approach which had been applied on similar tasks was adopted to analyze the complete database and create predictive models for the same 12 target variables. The values predicted by the intuitive reasoner and the reference approach were compared with actual data. The intuitive reasoner reached near-100% accuracy for two continuous target variables. For the discrete target variables, the intuitive reasoner predicted at least 70% as accurately as the reference reasoner. Since the intuitive reasoner operated on rules derived from only about 10% of the total data, it demonstrated the potential advantages in dealing with sparse data sets as compared with conventional methods.

Keywords: Artificial intelligence, intuition, knowledge acquisition, limited certainty.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1350
7552 Variable Rough Set Model and Its Knowledge Reduction for Incomplete and Fuzzy Decision Information Systems

Authors: Da-kuan Wei, Xian-zhong Zhou, Dong-jun Xin, Zhi-wei Chen

Abstract:

The information systems with incomplete attribute values and fuzzy decisions commonly exist in practical problems. On the base of the notion of variable precision rough set model for incomplete information system and the rough set model for incomplete and fuzzy decision information system, the variable rough set model for incomplete and fuzzy decision information system is constructed, which is the generalization of the variable precision rough set model for incomplete information system and that of rough set model for incomplete and fuzzy decision information system. The knowledge reduction and heuristic algorithm, built on the method and theory of precision reduction, are proposed.

Keywords: Rough set, Incomplete and fuzzy decision information system, Limited valued tolerance relation, Knowledge reduction, Variable rough set model

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1560
7551 DMC with Adaptive Weighted Output

Authors: Ahmed Abbas, M.R. M Rizk, Mohamed El-Sayed

Abstract:

This paper presents a new adaptive DMC controller that improves the controller performance in case of plant-model mismatch. The new controller monitors the plant measured output, compares it with the model output and calculates weights applied to the controller move. Simulations show that the new controller can help improve control performance and avoid instability in case of severe model mismatches.

Keywords: Adaptive control, dynamic matrix control, DMC, model predictive control

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2192
7550 Segmentation of Piecewise Polynomial Regression Model by Using Reversible Jump MCMC Algorithm

Authors: Suparman

Abstract:

Piecewise polynomial regression model is very flexible model for modeling the data. If the piecewise polynomial regression model is matched against the data, its parameters are not generally known. This paper studies the parameter estimation problem of piecewise polynomial regression model. The method which is used to estimate the parameters of the piecewise polynomial regression model is Bayesian method. Unfortunately, the Bayes estimator cannot be found analytically. Reversible jump MCMC algorithm is proposed to solve this problem. Reversible jump MCMC algorithm generates the Markov chain that converges to the limit distribution of the posterior distribution of piecewise polynomial regression model parameter. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of piecewise polynomial regression model.

Keywords: Piecewise, Bayesian, reversible jump MCMC, segmentation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1637
7549 Model-Based Software Regression Test Suite Reduction

Authors: Shiwei Deng, Yang Bao

Abstract:

In this paper, we present a model-based regression test suite reducing approach that uses EFSM model dependence analysis and probability-driven greedy algorithm to reduce software regression test suites. The approach automatically identifies the difference between the original model and the modified model as a set of elementary model modifications. The EFSM dependence analysis is performed for each elementary modification to reduce the regression test suite, and then the probability-driven greedy algorithm is adopted to select the minimum set of test cases from the reduced regression test suite that cover all interaction patterns. Our initial experience shows that the approach may significantly reduce the size of regression test suites.

Keywords: Dependence analysis, EFSM model, greedy algorithm, regression test.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1891
7548 Model of the Increasing the Capacity of the Train and Railway Track by Using the New Type of Wagon

Authors: Martin Kendra, Jaroslav Mašek, Juraj Čamaj, Martin Búda

Abstract:

The paper deals with possibilities of increase train capacity by using a new type of railway wagon. In the first part is created a mathematical model to calculate the capacity of the train. The model is based on the main limiting parameters of the train - maximum number of axles per train, maximum gross weight of train, maximum length of train and number of TEUs per one wagon. In the second part is the model applied to four different model trains with different composition of the train set and three different average weights of TEU and a train consisting of a new type of wagons. The result is to identify where the carrying capacity of the original trains is higher, respectively less than a capacity of train consisting of a new type of wagons.

Keywords: Loading units, theoretical capacity model, train capacity, wagon for intermodal transport.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2368
7547 Design of a Non-linear Observer for VSI Fed Synchronous Motor

Authors: P. Ramana , K. Alice Mary, M. Surya Kalavathi, M. Phani Kumar

Abstract:

This paper discusses two observers, which are used for the estimation of parameters of PMSM. Former one, reduced order observer, which is used to estimate the inaccessible parameters of PMSM. Later one, full order observer, which is used to estimate all the parameters of PMSM even though some of the parameters are directly available for measurement, so as to meet with the insensitivity to the parameter variation. However, the state space model contains some nonlinear terms i.e. the product of different state variables. The asymptotic state observer, which approximately reconstructs the state vector for linear systems without uncertainties, was presented by Luenberger. In this work, a modified form of such an observer is used by including a non-linear term involving the speed. So, both the observers are designed in the framework of nonlinear control; their stability and rate of convergence is discussed.

Keywords: Permanent magnet synchronous motor, Mathematicalmodelling, Rotor reference frame, parameter estimation, Luenbergerobserver, reduced order observer, full order observer

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1830
7546 Modeling and Simulation Methods Using MATLAB/Simulink

Authors: Jamuna Konda, Umamaheswara Reddy Karumuri, Sriramya Muthugi, Varun Pishati, Ravi Shakya,

Abstract:

This paper investigates the challenges involved in mathematical modeling of plant simulation models ensuring the performance of the plant models much closer to the real time physical model. The paper includes the analysis performed and investigation on different methods of modeling, design and development for plant model. Issues which impact the design time, model accuracy as real time model, tool dependence are analyzed. The real time hardware plant would be a combination of multiple physical models. It is more challenging to test the complete system with all possible test scenarios. There are possibilities of failure or damage of the system due to any unwanted test execution on real time.

Keywords: Model Based Design, MATLAB, Simulink, Stateflow, plant model, real time model, real-time workshop, target language compiler.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1659