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检索条件"主题词=whale optimization algorithm"

共 1221 条记录，以下是461-470 订阅

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Comparative Parameter Estimation of Single Diode PV-Cell Model by Using Sine-Cosine algorithm and whale optimization algorithm 6

Comparative Parameter Estimation of Single Diode PV-Cell Mod...

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6th International Conference on Electrical and Electronics Engineering (ICEEE)

作者： Aydin, Omer Gozde, Haluk Dursun, Mahir Taplamacioglu, M. Cengiz Gazi Univ Fac Engn Dept Elect & Elect Engn Ankara Turkey Natl Def Univ Turkish Mil Acad Elect & Commun Engn Dept Ankara Turkey

ISBN: (纸本)9781728139104

The share of photovoltaic energy systems in electricity production is increasing day by day. Photovoltaic systems are typically modeled as PV-cell circuit when using in power system analysis. The selection of the parameters used in the model is crucial because how close the model outputs are to reality depends on true estimation of these parameters. These parameters are also important for efficiency and maximum power tracking. Due to the increase in electricity generation with solar energy, the problem of estimation of these parameters has become a widely studied subject in recent years. In this study, the parameters of PV-cell are estimated using whale optimization algorithm (WOA) and Sine-Cosine algorithm (SCA) and compared with the related literature.

关键词： photovoltaic cells whale optimization algorithm sine-cosine algorithm parameter estimation

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Optimal Allocation of Distributed Generation in A Part of The Egyptian Electrical Network Using whale optimization algorithm 21

Optimal Allocation of Distributed Generation in A Part of Th...

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21st International Middle East Power Systems Conference (MEPCON)

作者： Zeuhom, Z. M. Boghdady, T. A. Abram Canadian Univ Giza Elect Power Engn Dept Giza Egypt Cairo Univ Elect Power Engn Dept Giza Egypt

ISBN: (纸本)9781728152899

The Distributed Generation (DG) relaying on generating units with small ratings to be linked into the distribution network close to the consumers. It can provide a promising future for power generation in electric networks. Recently, the demand for distributed generation into the electrical networks is rapidly increasing. Connecting DG units into the distribution networks can provide environmental, economic and technical merits. Those merits can be optimized if the DG unit site and size is properly determined. This paper presents a proposed multi-objective approach for determining the optimal allocation of the DG to enhance the voltage profile and minimizing the total active power loss of the distribution system. A recent optimization technique, whale optimization algorithm (WOA), is presented. A portion of the Egyptian electric network in the East Delta is introduced for testing the proposed algorithm via MatLab software.

关键词： Distributed generation Loss reduction Radial distribution network whale optimization algorithm

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Solving 0/1 Knapsack Problem using Opposition-based whale optimization algorithm (OWOA) 19

Solving 0/1 Knapsack Problem using Opposition-based Whale Op...

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8th International Conference on Software and Computer Applications (ICSCA)

作者： Alamri, Hammoudeh S. Zamli, Kamal Z. Ab Razak, Mohd Faizal Firdaus, Ahmad Univ Malaysia Pahang Fac Comp Syst & Software Engn Pahang Malaysia

ISBN: (纸本)9781450365734

The 0/1 Knapsack problem is one of the most popular real-world optimization problems that arise in searching space and finding the most optimum solution. Theoretically, the optimum solution problem of the 0/1 Knapsack requires suitable technique to explore the search space effectively. Practically, as many metaheuristic algorithms, whale optimization algorithm (WOA) may fail in local optimum solution. This paper proposes Opposition-based whale optimization algorithm (OWOA) to optimize solution problem in 0/1 Knapsack. The OWOA has been tested original WOA by using twenty cases of Knapsack problem and against other metaheuristic algorithms such as (CGMA) and HS-Jaya. The experimental results indicate a significant performance of the optimization solution and stabilization with minimal standard deviation value. This shows that the OWOA improved the original version WOA and has promising result in comparison with other existing algorithms.

关键词： 0\1 knapsack WOA whale optimization algorithm optimization Metaheuristic Real-World optimization Problem

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A modified whale optimization algorithm based on Chaos Initialization and Regulation Operation 38

A modified Whale Optimization Algorithm based on Chaos Initi...

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38th Chinese Control Conference (CCC)

作者： Jiang Ruiye Chao Tao Wang Songyan Yang Ming Harbin Inst Technol Harbin 150001 Peoples R China

ISBN: (纸本)9789881563972

A rising meta-heuristic swarm intelligent computation algorithm, the whale optimization algorithm (WOA), which has been proved competitive with other intelligent optimization algorithms in solving different optimization problems. To accelerate the convergence rate of WOA, this paper has proposed a new improved whale optimization algorithm, called Chaos Regulation whale optimization algorithm (CRWOA). The chaotic map generator composed with three kinds of chaotic maps has been used to initialize the population. Furthermore, Cauchy distribution and Gauss distribution are introduced to regulate the position in each iteration. To analyze the superiority of CRWOA further, ten single-objective benchmark test functions are chosen. Through the comparison and analysis of the optimal results, CRWOA is demonstrated superior in general. It has faster convergence speed and better results than the other algorithms when less iteration number, less population quantity and wider ranges of variables are set.

关键词： Benchmark functions Chaotic map Computation intelligence Continuous probability distribution whale optimization algorithm

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whale optimization algorithm based Edge Detection for Noisy Image 2

Whale Optimization Algorithm based Edge Detection for Noisy ...

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2nd International Conference on Intelligent Computing and Control Systems (ICICCS)

作者： Gautam, Aditya Biswas, Mantosh Natl Inst Technol Dept Comp Engn Kurukshetra Haryana India

ISBN: (纸本)9781538628423

Edge in image processing is considered as those pixels whose intensity value changes drastically and finding the object boundary is the main task of any edge detection technique. There have been various Ant Colony optimization (ACO), Particle Swarm optimization (PSO) based techniques that have been applied to solve edge detection problem, but most of them have not considered the noisy environment which in itself makes edge detection further more difficult task and the user-defined threshold approach doesn't always give desired results. The paper proposes a whale optimization algorithm (WOA) based edge detection technique with weighted fitness function including homogeneity, uniformity and average gradient magnitude as main factors for detecting the edges of additive gaussian noise images. The experiment results have shown that the proposed technique has performed better under noisy environment for conventional edge detectors: Sobel, Canny and ACO based technique for both objective criteria i.e. restored edge images and subjective criteria i.e. PSNR, Precision, Recall and F-measure.

关键词： Edge Detection whale optimization algorithm Gaussian Noise Homogeneity operator

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Analysis of Different Binarization Techniques within whale optimization algorithm

Analysis of Different Binarization Techniques within Whale O...

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Innovations in Intelligent Systems and Applications Conference (ASYU)

作者： Golcuk, Ilker Ozsoydan, Fehmi Burcin Durmaz, Esra Duygu Izmir Bakircay Univ Dept Ind Engn Izmir Turkey Dokuz Eylul Univ Dept Ind Engn Izmir Turkey Gazi Univ Dept Ind Engn Ankara Turkey

ISBN: (纸本)9781728128689

In this study, whale optimization algorithm (WOA), which is a recently proposed swarm intelligence-based algorithm, has been used to solve binary optimization problems. As the WOA algorithm has been developed for optimizing realvalued functions, binary versions of the WOA algorithm have been adopted for the binary optimization problems. The performance of modulation-, normalization-, s-shaped transfer function-, and angle modulation-based binarization approaches are compared. The proposed algorithms tested on the well-known benchmark problems, namely one-max, plateau, deceptive, and royal road. Our computational experiments show that angle modulation and normalization-based binarization approaches give the best results, and binary WOA is promising and has potential to handle difficult binary optimization problems.

关键词： binary optimization binarization techniques whale optimization algorithm

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A Spark-based Distributed whale optimization algorithm for Feature Selection 10

A Spark-based Distributed Whale Optimization Algorithm for F...

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10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems - Technology and Applications (IDAACS)

作者： Chen, Hongwei Hu, Zhou Han, Lin Hou, Qiao Ye, Zhiwei Yuan, Jiansen Zeng, Jun Hubei Univ Technol Sch Comp Sci Wuhan 430068 Peoples R China Wuhan Fiberhome Tech Serv Co Ltd Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9781728140698

With the rapid development of the Internet and big data technologies, high-dimensional data generated in various fields has increased dramatically. Feature selection is an effective way to solve data processing problems caused by high dimensionality and high computational complexity. The traditional feature selection method shows the problem of insufficient classification accuracy and low processing efficiency when dealing with high-dimensional and large-scale data. The traditional feature selection method shows low classification accuracy and low processing efficiency when dealing with high-dimensional and large-scale data. This paper proposed a feature selection method based on whale optimization algorithm to learn mining feature selection rules, then improve the accuracy of feature selection. However, when the data size is very large, the efficiency of single node execution is low. Therefore, this paper combined the whale optimization algorithm with the parallel computing model of the Spark platform, and proposed a feature selection method based on the Spark platform for distributed whale optimization algorithm. The results showed that the excellent result search ability of the whale optimization algorithm combined with the distributed and efficient calculation speed can realize the efficient solution of the feature selection optimization model.

关键词： feature selection whale optimization algorithm Spark platform parallel computing

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Tuning of SMC Parameters for Robotic Manipulator Based on whale optimization algorithm 2

Tuning of SMC Parameters for Robotic Manipulator Based on Wh...

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2nd World Robot Conference (WRC) / Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Du, Meilin Guo, Zuhua Meng, Cai Beihang Univ Sch Astronaut 37 Xueyuan Rd Beijing Peoples R China

ISBN: (纸本)9781728155524

A 2-link robotic manipulator is selected as a research instance, a sliding mode control(SMC) law is designed. Parameters tuning of sliding mode controller is converted to a nonlinear optimization problem with the objects of minimizing the trajectory tracking error and eliminating chattering of the control torques. The whale optimization algorithm (WOA) is adopted in this paper to obtain the best parameters of controller, and a comparative study with the results that are searched by particle swarm optimization (PSO) is made. Through simulation of the manipulator, control effects of the parameters obtained by the two optimization methods are compared. Research shows that WOA is a viable optimization method for parameter tuning of sliding mode control of robotic manipulator, and the optimization model proposed in this paper can effectively eliminate the chattering problem of control torques.

关键词： whale optimization algorithm Sliding Mode Control Robotic Manipulator Control Nonlinear optimization

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whale optimization algorithm for Constrained Economic Load Dispatch Problems-A Cost optimization

Whale Optimization Algorithm for Constrained Economic Load D...

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2nd International Conference on Recent Advancement in Computer, Communication and Computational Sciences (RACCCS)

作者： Kumar, Arvind Bhalla, Vikas Kumar, Praveen Bhardwaj, Tanuj Jangir, Narottam Govt Coll Engn & Technol Dept Elect Engn Bikaner 334004 Rajasthan India

ISBN: (纸本)9789811073861;9789811073854

This paper presents an optimization approach, population-based meta-heuristics algorithm, known as whale optimization algorithm (WOA) for constrained economic load dispatch problems. An overall solution of constrained economic load dispatch problems is providing a continuous and reliable supply of electricity while maintaining the optimal cost of production and operation for the system. The proposed whale optimization algorithm (WOA), which is based on the concept of bubble-net hunting strategy, is applied to standard benchmark test function and both IEEE test systems with the number of 6 thermal units, and 15 thermal units including ramp rate limits and prohibited operation zones. The WOA results have been compared with PSO and Lagrange's algorithm. The proposed algorithm is considerably fast and provides feasible near-optimal solutions. Simulation results have proved the performance of the proposed WOA algorithm to solve ELD problem within a faster convergence and reasonable execution time.

关键词： optimization whale optimization algorithm Economic load dispatch Power loss Fuel cost Prohibited operation zones

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Active Disturbance Rejection Control Tuned by whale optimization algorithm for Electric Loading System

Active Disturbance Rejection Control Tuned by Whale Optimiza...

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第三十九届中国控制会议

作者： Jiaqi Chang Dongkai Shen Dong Chen School of Automation Science and Electrical Engineering Beihang University Aviation Military Representative Office of Army Equipment Department in Chengdu

The torque load test is one of the key tests in the development of aircraft sidestick. Due to the coupling effect of mechanical structure, the angle produced by aircraft sidestick itself will affected the loaded torque of electric loading system, so that the surplus torque appears. In this paper, a control method is proposed to eliminate the surplus torque of loading device for aircraft sidestick. Active disturbance rejection control（ADRC） uses the extended state observer to collect all the nonlinear uncertainties for compensation. In order to avoid the negative influence of strong coupling of ADRC control parameters, whale optimization algorithm（WOA） is combined to automatically tune the parameters for the state of minimum surplus torque. The simulation results show that compared with PID control, the ADRC tuned by WOA can reduce the influence of sidestick angle disturbance, thus it satisfies the requirement for less surplus torque.

关键词： Active Disturbance Rejection Control whale optimization algorithm Surplus Torque Elimination Aircraft Sidestick

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