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The Imperialist Competitive Algorithm (ICA) that was recently introduced has shown its good performance in optimization problems. This novel optimization algorithm is inspired by socio-political process of imperialistic competition in the real world. In this paper a new Imperialist Competitive Algorithm using chaotic maps (CICA) is proposed. In the proposed algorithm, the chaotic maps are used to...
ANN using BP is widely used in power load forecasting. But there are some existed problem of the BP algorithm: (1) Convergence speed is slow, usually convergence needs more than one thousand times; (2) Objective function is prone to getting into local minimum.. How to overcome the shortcoming that convergence speed is slow and network is prone to trapping in local minimum has not been resolved. Training...
The sensitive dependence on initial conditions found in nonlinear chaotic systems is known as the ??butterfly effect??. Such systems when numerically analyzed can exhibit a convergence instability when employing standard numerical methods. Presented here is a practical numerical method for eliminating the ??under-resolution?? problem observed when solving for solutions to nonlinear chaotic systems...
Based on standard particle swarm optimization, the centroid of particle swarm is introduced in particle swarm optimization to enhance inter-particle cooperation and information sharing capabilities, then combining with ergodicity of the chaotic motion and fast convergence of the simplex algorithm, an improved hybrid particle swarm cooperative optimization algorithm is proposed to improve global optimum...
According to the characteristics of Artificial Fish-swarm Algorithm and Chaos Optimization Algorithm, A kind of artificial Fish-Swarm Algorithm with Chaos is constructed by adding chaos to influence the update of the velocities of artificial fish, so that precocious phenomenon is suppressed, the convergence rate and the accuracy is improved. By testing two functions and NP hard problems of the Planar...
The distribution network fault recovery described, made light of the actual distribution network recovery objective function, the analysis of genetic algorithms and ant colony algorithm based on the combination of genetic algorithms and ant colony count of the respective merits of proposed A genetic algorithm into the new strategy of ant colony algorithm using the genetic algorithm has stronger global...
The classical genetic algorithm is improved. The initial solutions are got by Hamming-Range algorithm to WTA problem. The principal of best to best is used in the individual match for the crossover operation. The selection of the crossover points is made out by chaotic series. Chaotic series is also applied in the mutation. We get the solution of WTA problem with the improved algorithm, and check...
The paper presents a new hybrid global optimization algorithm based on chaos search and complex method for nonlinear constrained optimization problems. To fit for chaos optimization algorithm, a constrained optimization problem is transformed into an unconstrained problem by penalty function method. The mapping mode of standard complex method is improved to solve the problem of low computational efficiency...
The PID control parameters are very important to performance of hydraulic servo control system and how to find rapidly the optimum values of PID control parameters is very difficult problem. To overcome the problem of low convergence speed and sensitivity to local convergence with the traditional quantum-behaved particle swarm optimization (QPSO) to handle optimum problem, a novel method of judging...
Particle Swarm Optimization (PSO) is an efficient, simple and fertile Optimization Algorithm. However, it suffers from premature convergence; moreover, the performance of PSO depends significantly on its parameters settings. PSO attracts attention from researchers; they try to improve algorithm performance and avoid its weakness. In this paper, we propose a new methodology that uses chaotic agents...
In this paper, we combined chaotic search into standard particle swarm search into one and proposed a new algorithm named as chaos particle swarm optimization algorithm(CPSO). The CPSO algorithm may speed the search process, and improve the ability of seeking the global optimal solution and convergence. And the CPSO algorithm was applied to analysis of one-dimensional tracing test date of river stream...
Based on classical PSO (abbreviated for particle swarm optimization) algorithm and quantum theory, this paper proposes an improved quantum particle swarm optimization algorithm - zbQPSO (abbreviated for zhao Bezier quantum-behaved PSO) algorithm. Identical particle system is introduced to update the position of particle, hyper-chaotic thought introduced to chaotic search for every particle and average...
An improved differential evolution algorithm is given. In the algorithm a logarithm increased crossover and a random migration operator are used to overcome the convergent slowness in the later period of the iteration and fall easily into premature convergence. It is shown by the experiments on eight typical problems that the modified algorithm has strongly global search ability.
Aimed to the problems of multivariable and complicated multi-objective function and constraint conditions in mechanical optimal design, a general finding solution method (namely, grey chaotic PSO algorithm) is introduced to high dimension multi-objective hybrid discrete variables and multiobjective function is transformed into single objective function by absolute degree of grey incidences. The model...
The efficient method to assess the static voltage stability is maximum loadability limit (MLL). Loadability problem is formulated as an optimization problem considering both equality and inequality constraints. Three particle swarm optimization (PSO) techniques namely general PSO, Adaptive PSO (APSO) and Chaotic PSO (CPSO) are developed to obtain maximum loadability limit under voltage limits and...
Artificial fish swarm algorithm (AFSA) is a kind of swarm intelligence algorithms, which has the features of not strict to parameter setting, insensitive to initial values, strong robustness and so on. But the precision can not be very high and artificial fish (AF) often suffers the problem of being trapped in local optima. Especially when the objective function is a multimodel function, this problem...
As an effective tool for optimization, differential evolution (DE) has aroused much interest. But the premature convergence of it often gives rise to erroneous results so should be improved. In this paper, a novel differential evolutionary algorithm (DECH) based on chaos local search (CLS) is proposed, which divides DE algorithm into two stages. Firstly, DECH runs with original DE model 'DE/best/1/bin'...
In this paper, a chaotic cooperative particle swarm optimization based on tent map (TCCPSO) is proposed. The cooperative particle swarm optimization (CPSO), can significantly improve the performance of the original algorithm. However, CPSO has the defect of leading to pseudominimizer, which can not be easily escaped by interleaving the CPSO and PSO algorithm. Therefore, we take full advantages of...
During the iterative process of standard particle swarm optimization (PSO), the premature convergence of particles decreases the algorithm's searching ability. Through analyzing the reason of particle premature convergence during the renewal process, by introducing the selection strategy based on antibody density and initiation based on equal probability chaos, chaos immune particle swarm optimization...
This paper proposes the chaos-genetic algorithm (CGA) based on the cat map in order to optimize a multidimensional and multimodal non-linear cost function for the seismic wavelet. The algorithm uses the initial sensitivity of the cat map to expand the scope of the search, and uses the ergodicity of the cat map to search the chaotic variables. Thus, reduces the data redundancy, maintains the diversity...
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