Results 221 to 230 of about 17,803 (264)

Research on Improvement of Particle Swarm Optimization

2019
Although the particle swarm optimization algorithm has simple principle, few parameters and easy implementation, the particle swarm optimization algorithm is easy to fall into local optimum on multi-mode function and the local search ability is relatively weak. In this paper, the improvement of these two defects is carried out.
Chunguang Chang, Xi Wu
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Improving cascading classifiers with particle swarm optimization

Eighth International Conference on Document Analysis and Recognition (ICDAR'05), 2005
This paper addresses the issue of class related reject thresholds for cascading classifier systems. It has been demonstrated in the literature that class related reject thresholds provide an error-reject tradeoff better than a single global threshold. In this work we argue that the error-reject tradeoff yielded by class-related reject thresholds can be
Luiz S. Oliveira, Alceu de Souza Britto Jr., Robert Sabourin   +2 more
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An improved particle swarm optimization by hybriding with JADE

2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), 2017
To overcome the weakness of particle swarm optimization (PSO), this study proposed an improvement of PSO by hybriding the adaptive differential evolution with optional external archive (JADE), named PSOJADE, to balance the global and local search capabilities. To evaluate the effectiveness of the algorithm, in the experiments, the proposed algorithm is
Sheng-Yong Du, Zhao-Guang Liu
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An Improved Particle Swarm Optimization

Applied Mechanics and Materials, 2013
By analyzing the current Particle Swarm Optimization, especially the analysis of weighting coefficient descending and random disturbance term improving, an improved Particle Swarm Optimization combining periodic weighting adjustment and random disturbance was put forward and its effectiveness is verified by experiments in this article.
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An Improved Particle Swarm Optimization for Continuous Problems

2009 Fifth International Conference on Natural Computation, 2009
This paper describes an improved particle swarm optimization (PSO) algorithm that combines stochastic local search (SLS) heuristics,named PSOSLS, to solve costly procedure of search and premature convergence for continuous function optimization problems. The SLS is embedded in the PSO to improve the proposed heuristics. During the global search process,
Ling Hao, Lishuan Hu
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Dynamic-PSO: An improved particle swarm optimizer

2015 IEEE Congress on Evolutionary Computation (CEC), 2015
In this paper, a variant of particle swarm optimization (PSO) is presented to handle the problem of stagnation encounters in PSO which may lead to get it trapped in local optima and premature convergence particularly in multimodal problems. The proposed scheme Dynamic-PSO (DPSO) does not disturb the fast convergence characteristics of PSO by keeping ...
Nitin Saxena 0002, Ashish Tripathi, K. K. Mishra 0001, Arun Kumar Misra   +3 more
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An Improved Particle Swarm Optimization for Complex Optimization Problems

2013
An improved particle swarm optimization (IPSO) is proposed where a general center particle is incorporated into particle swarm optimization (PSO) with linearly decreasing inertia weight factor in this paper. The general center particle is formed by the center of the best-found positions of all particles in IPSO.
Kezong Tang, Binxiang Liu, Jia Zhao 0001
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Improved hybrid particle swarm optimization algorithm

2010 Sixth International Conference on Natural Computation, 2010
Particle swarm optimization algorithm(PSO, in short) is a heuristic global optimization algorithm based on swarm intelligence. Each particle of the swarm represents one candidate solution of the optimization problem. PSO searches the optimal region of optimization space through the interaction of particles.
Huoming Zhang, Mingzheng Gao, Xiaofei Zhang   +2 more
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A refinement mechanism to improve particle swarm optimization

2016 IEEE Congress on Evolutionary Computation (CEC), 2016
Due to its simplicity and effectiveness in solving many optimization problems, Particle Swarm Optimization (PSO) has attracted the attention of many researchers in the last few years. Nonetheless, in more complicated problems (involving multi-modality, non-separable, etc.), the use of PSO becomes limited and sometimes impractical.
Wei Ren Tan, Saúl Zapotecas Martínez, Hernán E. Aguirre, Kiyoshi Tanaka   +3 more
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A New Approach to Improve Particle Swarm Optimization

2003
Particle swarm optimization (PSO) is a new evolutionary computation technique. Although PSO algorithm possesses many attractive properties, the methods of selecting inertia weight need to be further investigated. Under this consideration, the inertia weight employing random number uniformly distributed in [0,1] was introduced to improve the performance
Liping Zhang, Huanjun Yu, Shangxu Hu
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