- Category:
- matlab
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- File Size:
- 5kb
- Update:
- 2018-09-26
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- 李彤tongtong
Description: 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
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| Filename | Size | Date |
|---|
| 粒子群\Copy_of_main.m | 568 | 2018-09-03
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| 粒子群\Decisfun.m | 564 | 2018-09-03
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| 粒子群\mayi.m | 1309 | 2018-09-04
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| 粒子群\Minforedynprog.m | 2954 | 2018-09-03
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| 粒子群\SAPSO.m | 2398 | 2018-09-03
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| 粒子群\Stageobjfun.m | 8208 | 2018-09-03
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| 粒子群\Statetransfun.m | 109 | 2018-09-03
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| 粒子群 | 0 | 2018-09-04 |
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