Results 241 to 250 of about 127,515 (294)

Stochastic Approximation Algorithms With Applications To Particle Swarm Optimization, Adaptive Optimization, And Consensus

, 2015
Quan Yuan
openalex   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Optimizing Particle Swarm Optimization algorithm

2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), 2014
Particle Swarm Optimization (PSO) algorithm has become more popular recently. It has been shown to be an effective optimization tool in most of the applications. In this paper, we have applied the PSO algorithm to a sample Artificial Neural Network (ANN) application, measured the improvement, and optimized the PSO parameters to improve results as much ...
Iraj Koohi, Voicu Z. Groza
openaire   +1 more source

An improved particle swarm optimization algorithm

2008 IEEE International Conference on Granular Computing, 2008
An improved Particle Swarm Optimization (IPSO) algorithm is proposed in this paper. In the algorithm, a premature estimate mechanism is introduced to judge whether the particles accumulate in a small region and tell the probability whether the swarm is trapped in a local optimum.
Ping Luo, null Ying Xu, null Lihai Yao, null Yaolin Lou   +3 more
openaire   +1 more source

Improved Particle Swarm Optimization algorithms for electromagnetic optimization

Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, 2008
Particle Swarm is a relatively novel approach for global stochastic optimization. In this paper some variations over the basic algorithm are proposed, with the aim of a more efficient search over the solution space obtained with a negligible overhead in both complexity and speed. The presented algorithms are then applied to a mathematical test function
MUSSETTA, MARCO, S. Selleri, P. Pirinoli, ZICH, RICCARDO, L. Matekovits   +4 more
openaire   +5 more sources

Three Sub-Swarm Particle Swarm Optimization Algorithm

2009 International Workshop on Intelligent Systems and Applications, 2009
In order to overcome the drawback of the standard PSO, such as being subject to falling into local optimization, an improved PSO algorithm based on three sub-swarms exchange is proposed. Firstly the method divides the whole swarm into three sub-swarms which evolve jointly according to three different models, that is, one evolves with the standard PSO ...
Ming-Ming Bai, Hui Sun, Lie-Yang Wu, Ze-Tao Jiang, Wen-Huan Wu   +4 more
openaire   +1 more source

Bacterial Particle Swarm Optimization Algorithm

Advanced Materials Research, 2011
The loss of the population diversity leads to the premature convergence in existing particle swarm optimization(PSO) algorithm. In order to solve this problem, a novel version of PSO algorithm called bacterial PSO(BacPSO), was proposed in this paper. In the new algorithm, the individuals were replaced by bacterial, and a new evolutionary mechanism was ...
Ming Li, Xue Ling Ji
openaire   +1 more source

Improved Particle Swarm Optimization Algorithm

2010 International Conference on Computational Intelligence and Software Engineering, 2010
Particle Swarm Optimization (PSO) is a new random computational method for tackling optimization functions. However, it is easily trapped into the local optimum when solving the complexity and high-dimensional problems, which makes the performance of PSO greatly reduced.
Ye Gao, Shan Li
openaire   +1 more source

Multivector particle swarm optimization algorithm

Soft Computing, 2019
This paper proposes an improved meta-heuristic algorithm called multivector particle swarm optimization (MVPSO) for solving single-objective optimization problems. MVPSO improves particle swarm optimization (PSO) algorithm by creating more possible solutions for each particle during the optimization process.
Hussam N. Fakhouri, Amjad Hudaib, Azzam Sleit   +2 more
openaire   +1 more source

A Particle Swarm Optimization Algorithm

Applied Mechanics and Materials, 2013
The basic and improved algorithms of PSO focus on how to effectively search the optimal solution in the solution space using one of the particle swarm. However, the particles are always chasing the global optimal point and such points currently found on their way of search, rapidly leading their speed down to zero and hence being restrained in the ...
Fei Hong Zhou, Zi Zhen Liao
openaire   +1 more source

Fuzzy Particle Swarm Optimization Algorithm

2009 International Joint Conference on Artificial Intelligence, 2009
In this paper, a novel fuzzy particle swarm optimization(NFPSO), in which inertia weight as well as the learning coefficient can be adaptively adjusted according to the control information translated from the fuzzy logic controller (FLC) during the search process, is presented by introducing a two-input and two-output FLC into the canonical particle ...
Dong-ping Tian, Nai-qian Li
openaire   +1 more source