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  • Category : Mathimatics-Numerical algorithms
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  • Update : 2015-04-21
  • Size : 6kb
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  • Author :h*****
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Particle swarm optimization (PSO) is a population based stochastic optimization techniques. Based on evolutionary algorithms compared with other groups, they are initialized to a random solution, iterative search through optimal solution. The difference is: the principle of survival of the fittest evolutionary computation to follow, while PSO simulation community. The potential of each solution expressed as a group of particles, each particle has its own position vector and the velocity vector, and a fitness determined by the objective function. All particles in the search space at a constant speed flight, by following the current search to find the optimal values ​ ​ of the global optimum. PSO simulation community has adopted the following three simple rules for the operation of individual particles: ① recently departed individuals, in order to avoid collisions. ② to the target. ③ fly to center groups. This is one of the basic concepts of particle swarm algorithm. PSO algori
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13\fun.m
..\y13_1.m
..\y13_2.m
..\y13_3.m
..\y13_4.m
..\y13_4_2.m
..\y13_4_3.m
..\y13_4_4.m
..\y13_4_5.m
..\y13_5.m
13
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