نتایج جستجو برای: chaotic particle swarm optimization

تعداد نتایج: 503636  

Journal: :Int. Arab J. Inf. Technol. 2015
Mohammad Javidi Roghiyeh Hosseinpour Fard

Today the Genetic Algorithm (GA) is used to solve a large variety of complex nonlinear optimization problems. However, permute convergence which is one of the most important disadvantages in GA is known to increase the number of iterations for reaching a global optimum. This paper, presents a new GA based on chaotic systems to overcome this shortcoming,. We employ logistic map and tent map as t...

2012
S. M. Moosavi

The main objective of this paper is to investigate the enhancement of power system stability via coordinated tuning of Power System Stabilizers (PSSs) in a multi-machine power system. The design problem of the proposed controllers is formulated as an optimization problem. Chaotic catfish particle swarm optimization (C-Catfish PSO) algorithm is used to minimize the ITAE objective function. The p...

Journal: :journal of computer and robotics 0
mojtaba gholamian faculty of computer and information technology engineering, qazvin branch, islamic azad university, qazvin, iran mohammad reza meybodi department of computer engineering and information technology, amirkabir university of technology, tehran, iran

so far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is particle swarm optimization (pso). prior some efforts by applying fuzzy logic for improving defects of pso such as trapping in local optimums and early convergence has been done. moreover to overcome the problem of i...

2009
Jiann-Horng Lin Li-Ren Huang

Artificial Bee Colony algorithm is an optimization algorithm based on the intelligent behavior of honey bee swarm. This paper presents Bee Swarm Optimization intended to introduce chaotic sequences and psychology factor of emotion into the algorithm. We define two emotions Bees could have, positive and negative, and correspond to two reaction to perception respectively. For avoiding premature c...

Journal: :Appl. Soft Comput. 2007
Hongbo Liu Ajith Abraham Maurice Clerc

Swarm intelligence (SI) is an innovative distributed intelligent paradigm whereby the collective behaviors of unsophisticated individuals interacting locally with their environment cause coherent functional global patterns to emerge. The intelligence emerges from a chaotic balance between individuality and sociality. The chaotic balances are a characteristic feature of the complex system. This ...

2012
Her-Terng Yau Tzu-Hsiang Hung Chia-Chun Hsieh

This study used the complex dynamic characteristics of chaotic systems and Bluetooth to explore the topic of wireless chaotic communication secrecy and develop a communication security system. The PID controller for chaos synchronization control was applied, and the optimum parameters of this PID controller were obtained using a Particle Swarm Optimization (PSO) algorithm. Bluetooth was used to...

2009
Leandro dos Santos Coelho Viviana Cocco Mariani Leandro dos Santos

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm driven by the simulation of a social psychological metaphor instead of the survival of the fittest individual. Based on the chaotic systems theory, this paper proposed a novel chaotic PSO combined with an implicit filtering (IF) local search method to solve economic dispatch problems. Since chaotic mapping enjo...

The nonlinear behavior analysis and chaos control for Duffing-Holmes chaotic system is discussed in the paper. In order to suppress the irregular chaotic motion, an optimal backstepping controller is designed. The backstepping method consists of parameters with positive values. The improper selection of the parameters leads to inappropriate responses or even may lead to instability of the syste...

2013
Faezeh Farivar Mohammad Ali Nekoui Mahdi Aliyari Shoorehdeli Mohammad Teshnehlab

Abstract In this paper, evolutionary algorithms are proposed to compute the optimal parameters of Gaussian Radial Basis Adaptive Backstepping Control (GRBABC) for chaotic systems. Generally, parameters are chosen arbitrarily, so in several cases this choice can be tedious. Also, stability cannot be achieved when the parameters are inappropriately chosen. The optimal design problems are to intro...

2012
W.-B. Wang Q.-Y. Feng D. Liu

Traditional optimization methods are not well suitable for thinning large arrays to obtain a low sidelobe level (SLL). The chaotic binary particle swarm optimization (CBPSO) algorithm is presented as a useful alternative for the synthesis of thinned arrays. The proposed algorithm can be improved by nonlinear inertia weight with chaotic mutation to increase the diversity of particles. Two exampl...

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