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Adaptive CR Values with Fuzzy Inference System for differential evolution algorithm

Adaptive CR Values with Fuzzy Inference System for Different...

IEEE Congress on evolutionary Computation (CEC) held as part of IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Wang, Jing-Zhong Sun, Tsung-Ying Natl Dong Hwa Univ Dept Elect Engn Hualien Taiwan

ISBN: (纸本)9781509006229

This study proposed fuzzy-based adaptive method for crossover rate (CR) values to improve the convergence rate of differential evolution (DE) algorithms. The proposed method decides the CR values according to two factors of the evolutionary environment, the change rate of solution of center of solutions and the density of each dimension. The proposed DE algorithm is tested by the CEC2015 benchmark suits and compared with fuzzy adaptive differential evolution (FADE). The experimental results showed that the proposed method really improved performance for 11 of 15 evaluated functions in 10, 30, and 50 dimensions and enhanced the convergence.

关键词： fuzzy fuzzy inference system adaptive crossover rate differential evolution algorithm

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Underwater Image Enhancement Based On Contrast Adjustment via differential evolution algorithm

Underwater Image Enhancement Based On Contrast Adjustment vi...

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International Symposium on Innovations in Intelligent Systems and Applications (INISTA)

作者： Guraksin, Gur Emre Kose, Utku Deperlioglu, Omer Afyon Kocatepe Univ Fac Engn Dept Biomed Engn Afyon Turkey Usak Univ Comp Sci Applicat & Res Ctr Usak Turkey Afyon Kocatepe Univ Vocat Sch Afyon Afyon Turkey

ISBN: (纸本)9781467399104

Due to the absorption and scattering of light in underwater environment, underwater images have poor contrast and resolution. This situation generally causes to a color, which became more dominant than the other ones. Because of that, analyzing underwater images effectively and identifying any object under the water has become a difficult task. In this paper, an underwater enhancement approach by using differential evolution algorithm was proposed. In the approach, a contrast enhancement in the RGB space is done. By using the approach, both scattering and absorption effects are reduced.

关键词： underwater image enhancement differential evolution algorithm contrast stretching optimization artificial intelligence

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differential evolution algorithm Based Load Frequency Control in a Two-Area Conventional and Renewable Energy Based Nonlinear Power System

Differential Evolution Algorithm Based Load Frequency Contro...

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International Conference on the Developments in Renewable Energy Technology

作者： Muhammad Ahsan Zamee Kazi Khairul Islam Ashik Ahmed Kazi Rehnuma Zafreen Department of Electrical and Electronic Engineering Bangladesh University 15/1 IqbalRoad Mohammadpur Dhaka-1207

ISBN: (纸本)9781467382557

Load Frequency Control (LFC) for any power generating station is a subject of great concern for power system researchers. With the changes of load demand, frequency starts fluctuating which results in deviation in tie line power flow and frequency deviation at consumer end. To overcome this problem, many control techniques have been adopted. In early days fixed value integral/proportional-integral control, Optimal Control, Quantitative feedback theory, pole placement etc. methods were applied. In recent times, neural network, fuzzy logic, genetic algorithm controllers are replacing the conventional techniques. All the control techniques are used to find the optimal values of the PID/PI controller gain parameters (K_p, K_i, K_d) for which system stability is confirmed with minimum of Area Control Error (ACE). differential evolution (DE) which is a newer branch of genetic algorithms has been successfully applied in this problem. In this paper DE based PI controller has been implemented for Hydro-Thermal power plants to find out the optimal value of gain parameters for system stability. Nonlinearity has been considered in governor part of the thermal area for practical scenario. 1% step load changes have been applied to both areas simultaneously and individually to confirm its performance. Desired set of controller gain parameters (K_p, K_i) are selected based on eigenvalue and minimum value of Objective Function. All simulations are done in the MATLAB/SIMULINK environment.

关键词： Load Frequency Control Automatic Generation Control Eigenvalue Objective Function differential evolution algorithm Proportional-Integral Controller

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An Improved differential evolution algorithm for Solving Absolute Value Equations 1

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3rd International Conference on High-Performance Computing and Applications (HPCA)

作者： Ning, Guiying Zhou, Yongquan Guangxi Univ Sci & Technol Lushan Coll Liuzhou 545616 Guangxi Peoples R China Guangxi Univ Nationalities Coll Math & Comp Sci Nanning 530006 Guangxi Peoples R China

ISBN: (数字)9783319325576

ISBN: (纸本)9783319325576;9783319325569

Absolute value equations Ax - vertical bar x vertical bar = b are non-differentiable hard problems. Many linear and quadratic programming problems can ultimately be converted into absolute value equation problems so research on solving an absolute value problem has important practical and theoretical significance. An improved adaptive differential evolution algorithm was proposed to solve the absolute value equations in this paper. The algorithm combined global search ability and local search ability, using an adaptive quadratic mutation operation and crossover operation. Numerical results show that the improved algorithm can quickly find the solutions of these equations.

关键词： Absolute value equations differential evolution algorithm Mutation operation Crossover operation Adaptive

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Parameter Estimation of a Space Radiator using differential evolution algorithm 9

Parameter Estimation of a Space Radiator using Differential ...

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9th International Conference on Contemporary Computing (IC3)

作者： Das, Ranjan Indian Inst Technol Ropar Dept Mech Engn Rupnagar 140001 Punjab India

ISBN: (纸本)9781509032518

In this article, different combinations of geometrical dimensions of a rectangular space radiator have been estimated using an inverse method. The solution procedure is based on the real-coded differential evolution (DE) optimization algorithm. Electronic equipments and aircraft power plants such as gas turbines need to be consistently cooled for safe operation and due to absence of air medium in space, the heat transfer occurs mainly by surface radiation. The required rate of heat to be dissipated is directly dependent upon the prevailing temperature distribution. Therefore, in this work, the estimation of parameters has been done for satisfying a predefined and simulated surface temperature profile on a space radiator. The temperature distribution used in the present inverse simulation study has been calculated and updated using the fourth order Runge-Kutta method and DE algorithm, respectively. Results have been validated against the existing literature. The present work reveals many possible combinations of the space radiator to attain a given temperature distribution. This offers the opportunity and flexibility to select a space radiator to achieve the required heat transfer rate for cooling various electronic equipments and power generating units typically for space applications.

关键词： space radiator Runge-Kutta method differential evolution algorithm inverse analysis

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differential evolution algorithm-BASED RANGE IMAGE REGISTRATION WITH SCALING PARAMETERS

DIFFERENTIAL EVOLUTION ALGORITHM-BASED RANGE IMAGE REGISTRAT...

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IEEE International Conference on Image Processing

作者： Taifeng Li Liang Gao Quanke Pan Peigen Li The State Key Laboratory of Digital Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science & Technology

ISBN: (纸本)9781467399623

Range image registration is used to align two or more three dimensional (3D) point sets into a common coordinate system. In the matching process, however, the influence of the resolution of 3D scans is ignored generally. In this paper, an enhanced differential evolution (DE) algorithm is proposed to align two different scaling 3D point sets. Specifically, Generalized Procrustes Analysis (GPA) method is employed to accelerate the DE in population initialization. In addition, a novel mutation technique is introduced to improve the accuracy for registration. The proposed method can evaluate all of the transformation parameters synchronously and it is effective for both isotropic and anisotropic scaling registration problem. Experiment results reveal that the proposed algorithm is much superior to other methods in terms of accuracy and robustness for scaling registration problem.

关键词： Range image Registration Transformation parameters differential evolution algorithm range image differential evolution algorithms Registration image registration Scale formation scale parameter Coordinate system

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differential evolution algorithm-based Kernel Parameter Selection for Fukunaga-Koontz Transform Subspaces Construction 5

Differential Evolution Algorithm-based Kernel Parameter Sele...

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Conference on High-Performance Computing in Remote Sensing V

作者： Binol, Hamidullah Bal, Abdullah Cukur, Huseyin Yildiz Tech Univ Dept Elect & Commun Engn TR-34220 Istanbul Turkey

ISBN: (纸本)9781628418569

The performance of the kernel based techniques depends on the selection of kernel parameters. That's why;suitable parameter selection is an important problem for many kernel based techniques. This article presents a novel technique to learn the kernel parameters in kernel Fukunaga-Koontz Transform based (KFKT) classifier. The proposed approach determines the appropriate values of kernel parameters through optimizing an objective function constructed based on discrimination ability of KFKT. For this purpose we have utilized differential evolution algorithm (DEA). The new technique overcomes some disadvantages such as high time consumption existing in the traditional cross-validation method, and it can be utilized in any type of data. The experiments for target detection applications on the hyperspectral images verify the effectiveness of the proposed method.

关键词： differential evolution algorithm Fukunaga-Koontz transform hyperspectral imagery kernel-based methods parameter selection

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Optimal design of proportional-integral controllers for stand-alone solid oxide fuel cell power plant using differential evolution algorithm

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SPRINGERPLUS 2016年第1期5卷 1页

作者： Ahmed, Ashik Ullah, Md. Shahid Islamic Univ Technol EEE Dept Boardbazar Gazipur Bangladesh

This paper proposes the application of differential evolution (DE) algorithm for the optimal tuning of proportional-integral (PI) controller designed to improve the small signal dynamic response of a stand-alone solid oxide fuel cell (SOFC) system. The small signal model of the study system is derived and considered for the controller design as the target here is to track small variations in SOFC load current. Two PI controllers are incorporated in the feedback loops of hydrogen and oxygen partial pressures with an aim to improve the small signal dynamic responses. The controller design problem is formulated as the minimization of an eigenvalue based objective function where the target is to find out the optimal gains of the PI controllers in such a way that the discrepancy of the obtained and desired eigenvalues are minimized. Eigenvalue and time domain simulations are presented for both open-loop and closed loop systems. To test the efficacy of DE over other optimization tools, the results obtained with DE are compared with those obtained by particle swarm optimization (PSO) algorithm and invasive weed optimization (IWO) algorithm. Three different types of load disturbances are considered for the time domain based results to investigate the performances of different optimizers under different sorts of load variations. Moreover, non-parametric statistical analyses, namely, one sample Kolmogorov-Smirnov (KS) test and paired sample t test are used to identify the statistical advantage of one optimizer over the other for the problem under study. The presented results suggest the supremacy of DE over PSO and IWO in finding the optimal solution.

关键词： Solid oxide fuel cell differential evolution algorithm Small signal model Eigen-value based objective function Particle swarm optimization algorithm and invasive weed optimization algorithm

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Multi-objective Optimization of a Parallel Ankle Rehabilitation Robot Using Modified differential evolution algorithm

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Chinese Journal of Mechanical Engineering 2015年第4期28卷 702-715页

作者： WANG Congzhe FANG Yuefa GUO Sheng School of Mechanical Electronic and Control Engineering Beijing Jiaotong University

Dimensional synthesis is one of the most difficult issues in the field of parallel robots with actuation redundancy. To deal with the optimal design of a redundantly actuated parallel robot used for ankle rehabilitation, a methodology of dimensional synthesis based on multi-objective optimization is presented. First, the dimensional synthesis of the redundant parallel robot is formulated as a nonlinear constrained multi-objective optimization problem. Then four objective functions, separately reflecting occupied space, input/output transmission and torque performances, and multi-criteria constraints, such as dimension, interference and kinematics, are defined. In consideration of the passive exercise of plantar/dorsiflexion requiring large output moment, a torque index is proposed. To cope with the actuation redundancy of the parallel robot, a new output transmission index is defined as well. The multi-objective optimization problem is solved by using a modified differential evolution（DE） algorithm, which is characterized by new selection and mutation strategies. Meanwhile, a special penalty method is presented to tackle the multi-criteria constraints. Finally, numerical experiments for different optimization algorithms are implemented. The computation results show that the proposed indices of output transmission and torque, and constraint handling are effective for the redundant parallel robot; the modified DE algorithm is superior to the other tested algorithms, in terms of the ability of global search and the number of non-dominated solutions. The proposed methodology of multi-objective optimization can be also applied to the dimensional synthesis of other redundantly actuated parallel robots only with rotational movements.

关键词： ankle rehabilitation parallel robot multi-objective optimization differential evolution algorithm

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A HYPERSPECTRAL BAND SELECTION BASED ON GAME THEORY AND differential evolution algorithm

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INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS 2016年第4期9卷 1971-1990页

作者： Shi, Aiye Gao, Hongmin He, Zhenyu Li, Min Xu, Lizhong Hohai Univ Coll Comp & Informat Engn Nanjing 211100 Jiangsu Peoples R China Hohai Univ Coll IOT Changzhou 213022 Peoples R China

This paper uses the combination of information and class separability as a new evaluation criterion for hyperspectral imagery. Moreover, the correlation between bands is used as a constraint condition. The differential evolution algorithm is adopted during the search of optimal band combination. In addition, the game theory is introduced into the band selection to coordinate the potential conflict of searching the optimal band combination using information and class separability these two evaluation criteria. The experimental results show that the proposed method is effective.

关键词： Remote Sensing Hyperspectral imagery band selection game theory differential evolution algorithm

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