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粒子群

  • Category : matlab
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  • Update : 2018-09-26
  • Size : 5kb
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  • Author :李彤tongtong
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Particle Swarm Optimization, also known as Particle Swarm Optimization or Particle Swarm Optimization, abbreviated as PSO, is a new evolutionary algorithm developed by J. Kennedy and RC Eberhart in recent years (Evolutionary Algorithm - EA). ). The PSO algorithm is a kind of evolutionary algorithm. It is similar to the simulated annealing algorithm. It also starts from the random solution and finds the optimal solution through iteration. It also evaluates the quality of the solution by fitness, but it is simpler than the rules of genetic algorithm. It does not have the "crossover" and "mutation" operations of the genetic algorithm, which seeks global optimality by following the current searched optimal values. This kind of algorithm has attracted the attention of academic circles because of its advantages of easy implementation, high precision and fast convergence
Packet file list
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FilenameSizeUpdate
粒子群\Copy_of_main.m 568 2018-09-03
粒子群\Decisfun.m 564 2018-09-03
粒子群\mayi.m 1309 2018-09-04
粒子群\Minforedynprog.m 2954 2018-09-03
粒子群\SAPSO.m 2398 2018-09-03
粒子群\Stageobjfun.m 8208 2018-09-03
粒子群\Statetransfun.m 109 2018-09-03
粒子群 0 2018-09-04
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