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检索条件"主题词=Real coded Genetic algorithm"

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Application of Fuzzy Cognitive Maps to water demand prediction

Application of Fuzzy Cognitive Maps to water demand predicti...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Papageorgiou, Elpiniki I. Poczeta, Katarzyna Laspidou, Chrysi CERTH Ctr Res & Technol Hellas Inst Informat Technol 6th Km Charilaou Thermi Rd Thermi 57001 Greece Technol Educ Inst TEI Cent Greece Dept Comp Engn Lamia 35100 Greece Kielce Univ Technol Dept Comp Sci Applicat Kielce Poland Univ Thessaly Dept Civil Engn Volos 38334 Volos Greece

ISBN: (纸本)9781467374286

This article is focused on the issue of learning of Fuzzy Cognitive Maps designed to model and predict time series. The multi-step supervised-learning based-on-gradient methods as well as population-based learning, with the use of real coded genetic algorithms, are described. In this study, a new structure optimization genetic algorithm for fuzzy cognitive maps learning is proposed for automatic construction of FCM applied to time series prediction. The proposed learning methodologies are based on an FCM reconstruction procedure using historical time series. The main contribution of this study is the analysis of the use of FCMs with their learning algorithms based on the multi-step gradient method (MGM) and other population-based methods to predict water demand. The performance of learning algorithms is presented through the analysis of real data of daily water demand and the corresponding prediction. The multivariate analysis of historical water demand data is held for five variables, mean and high temperature, precipitation, wind speed and touristic activity. Simulation results were obtained with the ISEMK (Intelligent Expert System based on Cognitive Maps) software tool. Through the experimental analysis, we demonstrate the usefulness of the new proposed FCM learning algorithm in water demand prediction, by calculating the known prediction errors. The advantage of the optimization genetic algorithm structure is its ability to select the most significant relations between concepts for prediction.

关键词： Fuzzy Cognitive Maps Multi-Step Learning algorithms Population-Based Learning algorithms real coded genetic algorithm Structure Optimization genetic algorithm Gradient Method

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Three-Dimensional Grain Design Optimization of Solid Rocket Motors 7

Three-Dimensional Grain Design Optimization of Solid Rocket ...

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7th International Conference on Recent Advances in Space Technologies (RAST)

作者： Yucel, Osman Acik, Sevda Toker, K. Atilgan Dursunkaya, Zafer Aksel, M. Haluk Roketsan Missiles Ind Inc Prop Syst Design Dept Ankara Turkey Middle East Tech Univ Dept Mech Engn Ankara Turkey

ISBN: (纸本)9781479976973

This study investigates the ballistic design optimization of three-dimensional grains of solid rocket motors (SRMs). The geometric modeling and burnback analysis of grains are performed analytically by using basic geometries like cylinder, cone, prism, sphere, ellipsoid, and torus. For the internal ballistic analysis, a quasi-steady zero-dimensional flow solver is used. Three different optimization methods are considered: real-coded genetic algorithm (GA), binary genetic algorithm and complex method. The optimization methods are applied to the problems of finding the parameters of grain geometry satisfying an objective thrust versus time profile and maximizing the parameter of total impulse satisfying the constraints of chamber pressure and propellant mass.

关键词： Solid rocket motor grain design burnback analysis optimization binary genetic algorithm real coded genetic algorithm complex method

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Hybrid Metaheuristic Particle Filters for Stochastic Volatility Estimation 12

Hybrid Metaheuristic Particle Filters for Stochastic Volatil...

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14th International Conference on genetic and Evolutionary Computation Conference (GECCO)

作者： Smith, Robert Elliott Hussain, Muhammad Shakir UCL Dept Comp Sci London WC1E 6BT England

ISBN: (纸本)9781450311779

In this paper we propose hybrid metaheuristic particle filters for the dual estimation of state and parameters in a stochastic volatility estimation problem. We use evolutionary strategies and real coded genetic algorithms as the metaheuristics. The hybrid metaheuristic particle filters provides more accurate results and uses lesser number of particles for this high dimension estimation problem. We compare the performance of our hybrid algorithms with a sequential importance resampling particle filter (SIR) and the parameter learning algorithm (PLA). Our hybrid particle filters out perform both these algorithms for this particular dual estimation problem.

关键词： real coded genetic algorithm evolution strategies covariance matrix adaption (CMA) algorithm particle filters (PF) stochastic volatility estimation Heston model

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Inference Strategies for Texture Parameters 20th

Inference Strategies for Texture Parameters

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20th Iberoamerican Congress on Pattern Recognition (CIARP)

作者： Martinez, Jorge Pistonesi, Silvina Georgina Flesia, Ana Univ Nacl Sur Dept Matemat RA-8000 Bahia Blanca Buenos Aires Argentina Univ Nacl Cordoba Fac Matemat Astron & Fis Ingn Medina Allende S-NCiudad Univ RA-5000 Cordoba Argentina

ISBN: (纸本)9783319257518;9783319257501

The Autobinomial model is a commonplace in Bayesian image analysis since its introduction as a convenient image model. Such model depends on a set of parameters;their value characterize texture allowing to perform classification of the whole image into regions with uniform properties of the model. This work propose a new estimator of the parameter vector of the Autobinomial model based on Conditional Least Square minimization via real coded genetic Modeling and analyze its performance compared to the classical linear approximation, which exchanges the CLS equation with a reduced Taylor equation prior to minimization. Our simulation study shows that the genetic modeling approach gives more accurate estimations when true data is provided. We also discuss its influence in a set of classification experiments with multispectral optical imagery, estimating the scalar vector parameter with our estimator and the classical linear one. Our experiments show promising results, since our approach is able to distinguish image features that the classical approach does not.

关键词： real coded genetic algorithm Conditional least squares method Gibbs Markov random field Autobinomial model Parameter estimation

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Performance comparison of Optimum uniform and non-uniform Spacing of Circular Antenna Arrays

Performance comparison of Optimum uniform and non-uniform Sp...

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International Conference on Communications, Devices and Intelligent Systems (COOlS)

作者： Ram, Gopi Biswas, Anik Mandal, Durbadal Kar, Rajib Ghoshal, Sakti Prasad Natl Inst Technol Durgapur Dept ECE Durgapur India

ISBN: (纸本)9781467346986;9781467346993

In this paper, comparative study of performance of radiation pattern with optimum non-uniform current amplitude excitations weights and optimum uniformly spaced circular array is compared with optimum non-uniform current amplitude excitations with optimum non-uniformly spaced circular array. The method of reduction of radiation pattern of a circular antenna array is hashed out using real coded genetic algorithm (RGA). Circular array antennas lying on x-y plane is assumed. The array is assumed to have the maximum radiation along positive z- axis. Single and multiple nulls are imposed by optimizing the current amplitude excitations and optimizing inter-element spacing of each element through RGA. Various simulated results are presented and hence performance of the radiation pattern is analyzed.

关键词： Circular array antennas First Null Beamwidth Side lobe Level real coded genetic algorithm

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SOS Based Solution for Optimization of Indian Power System 1

SOS Based Solution for Optimization of Indian Power System

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1st International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET)

作者： Chennaiah, P. Bala Nagendra, P. Vaisakh, K. AITS EEE Dept Rajampet India Dept Tech Educ EEE Dept Vijayawada Andhra Pradesh India Andhra Univ EEE Dept Visakhapatnam Andhra Pradesh India

ISBN: (纸本)9781728175492

This paper proposes a Symbiotic Organisms Search (SOS) algorithm based solution to optimize the control variables simultaneously to optimize the power system real power loss and voltage stability limit. This issue can be mathematically formulated as a problem of nonlinear equality and inequality limited optimization, with an objective function integrating real power loss and voltage stability limit. The problem formulation included transformers taps, unified power flow controller and its parameters as control variables. The efficacy of the proposed algorithm has been tested on Indian 24-bus system. The simulation results obtained with the proposed algorithm are compared with the real coded genetic algorithm (RCGA) for a single objective of minimizing real power loss and multi-objective minimization of real power loss and maximization of voltage stability. Results from simulation demonstrate the ability of the proposed algorithm in solving the optimization problem.

关键词： Symbiotic organisms search algorithm real power loss voltage stability limit real coded genetic algorithm unified power flow controller

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Novel Design of Fractional Delay Filter using Lattice Wave Digital Filter 1

Novel Design of Fractional Delay Filter using Lattice Wave D...

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1st IEEE International Conference on Power Electronics, Intelligent Control, and Energy Systems (ICPEICES)

作者： Barsainya, Richa Rawat, Tarun Kumar Bansal, Shivani Majhi, Arnesh Netaji Subhas Inst Technol Elect & Commun Engn Div Sect 3 New Delhi 110078 India

ISBN: (纸本)9781467385879

This paper deals with the application of lattice wave digital filter (LWDF) (3rd and 5th order) for obtaining an efficient design of a Fractional Delay Filter (FDF). The real coded genetic algorithm (RCGA) and Cuckoo Search algorithm (CSA) have been used in order to determine the optimal coefficient values of LWDF in order to meet the ideal frequency response characteristics. The simulation of FDF using LWDF structure improves the accuracy of design because of its excellent properties and also it needs only N number of multiplier coefficients for N6 order FDF. The simulation results of lattice wave digital Fractional delay filter (LWDFDF) are compared with infinite impulse response-fractional delay filter (IIR-FDF), also designed using RCGA and CSA and it is seen that LWDF based FD filter is superior to the 11R design.

关键词： Lattice Wave Digital Filter Infinite Impulse Response Filter Fractional Delay Filter real coded genetic algorithm Cuckoo Search algorithm

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Meta-Heuristic algorithms Based Multi-Level Thresholding 27

Meta-Heuristic Algorithms Based Multi-Level Thresholding

引用

27th Signal Processing and Communications Applications Conference (SIU)

作者： Kucukugurlu, Busranur Gedikli, Eyup Gumushane Univ Yazilim Muhendisligi Bolumu Gumushane Turkey Karadeniz Tech Univ Yazilim Muhendisligi Bolumu Trabzon Turkey

ISBN: (纸本)9781728119045

Thresholding is a very important stage in computer vision applications. An ideal single thresholding algorithm is not available for all environments. Multi-level thresholding in environments with multiple objects is constantly being developed for interpretation of images. Kapur entropy and Otsu approaches are among the most successful algorithms in the literature. In this study, it is tried to increase the performance of Otsu and Kapur algorithms by using meta-heuristic optimization approaches. The results of the Firefly algorithm (FF) and real coded genetic algorithm (RGA) were evaluated with PSNR, SSIM and CPU processing time criteria.

关键词： Firefly algorithm real coded genetic algorithm Otsu Method Kapur's Entropy Thresholding

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Application of Hybrid Modeling and Control Technique to a Non Linear Hybrid System

Application of Hybrid Modeling and Control Technique to a No...

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International Conference on Green Computing, Communication and Conservation of Energy (ICGCE)

作者： Ravi, V. R. Thyagarajan, T. Velammal Engn Coll Dept Elect & Instrumentat Engn Madras 600066 Tamil Nadu India Anna Univ Dept Instrumentat Engn Madras 600044 Tamil Nadu India

ISBN: (纸本)9781467361255

This paper presents a newer modeling and control implementation technique using multi state model approach for Two Tank Hybrid System (TTHS) which is a benchmark for nonlinear hybrid system. This class of hybrid system is a collection of sabsystems defined on different sob-space, which arc related by a switching logic. The MATLAB Simulink and Stateflow tools are used to formulate the multi state models and switching logic for TTHS. Three cases namely TTHS with single PID controller which is designed based on single linearized model. TTHS with as many PID controllers which are designed based on multiple linearized models and TTHS with as many PID controllers which are designed based on multi state model framework are considered. The real coded genetic algorithm is used to obtain the optimal PID control settings in all the three cases. The performances of the proposed PID control scheme based on multi state model framework using simulation on a TTHS are presented. The advantages of TTHS with PID control scheme based on multi state model approach over the other two cases are highlighted.

关键词： Non linear hybrid system Multi model control real coded genetic algorithm Multi state models Two Tank Hybrid System

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genetically Optimized Supplementary Controller for SSSC to Damp Subsynchronous Oscillations

Genetically Optimized Supplementary Controller for SSSC to D...

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1st International Conference on Information Systems Design and Intelligent Applications (INDIA 2012)

作者： Padhy, Sasmita Panda, Sidhartha Department of Electrical and Electronics Engineering National Institute of Science and Technology (NIST) Berhampur Odisha 761 008 India Department of Electrical and Electronics Engineering Veer Surendra Sai University of Technology (VSSUT) Burla Odisha 768018 India

ISBN: (纸本)9783642274428

A supplementary subsynchronous damping controller is proposed for the static synchronous series compensator (SSSC) device to damp out subsynchronous oscillations in power systems with series compensated transmission lines. The design problem of the proposed controller is formulated as an optimization problem, and real coded genetic algorithm is employed to search for the optimal controller parameters. It is shown that the controller is able to stabilize all unstable modes. The IEEE Second Benchmark Model is considered as the system under study. All the simulations are carried out in MATLAB/SIMULINK environment.

关键词： Subsynchronous resonance torsional oscillations static synchronous series compensator real coded genetic algorithm

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