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As an important parameter, up to day, many strategies for cognitive coefficient have been proposed. However, there is still some work need to do. Since each particle maintains different living experience e.g. feeding, nursing baby and so on. Thus different individual will make a different decision. However, this decision mechanism is not included in the improved particle swarm optimization (PSO)....
Particle swarm optimization (PSO) is a new swarm intelligent optimization technique. Although it maintains a fast convergent speed, it is still easy trapped into a local optimum when dealing with high-dimensional numerical problems. To overcome this shortcoming, in this paper, a new variant of PSO is designed hybrid with a dynamic population strategy and crossover operator. Simulation results show...
Premature convergence is a major problem of Particle Swarm Optimization (PSO).Although many strategies have been proposed, there is still some work needed to do in high-dimensional cases. To overcome this shortcoming, a diffused velocity update equation is designed aiming to improve the population diversity with a c. Simulation results show the performance of this new variant is superior to other...
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