文件名称:PSO_BP
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2012-11-26
- 文件大小：
- 23kb
- 下载次数：
- 0次
- 提 供 者：
- y***
- 相关连接：
- 无
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粒子群优化算法应用于神经网络优化程序。分为无隐含层、一隐含层、二隐含层。运行DemoTrainPSO.m即可-Particle swarm optimization applied to neural network optimization program. No hidden layer is divided into a hidden layer, two hidden layers. You can run DemoTrainPSO.m
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下载文件列表
粒子群优化算法（PSO）应用于神经网络优化程序。分为无隐含层、一隐含层、二隐含层。运行DemoTrainPSO.m即可
.....................................................................................................\DemoTrainPSO.m
.....................................................................................................\f6.m
.....................................................................................................\goplotpso.m
.....................................................................................................\hypara2.m
.....................................................................................................\normalize.m
.....................................................................................................\pso.m
.....................................................................................................\tpso1.m
.....................................................................................................\tpso2.m
.....................................................................................................\tpso3.m
.....................................................................................................\trainpso.m
.....................................................................................................\unwrapmat.m
.....................................................................................................\wrapmat.m
.....................................................................................................\DemoTrainPSO.m
.....................................................................................................\f6.m
.....................................................................................................\goplotpso.m
.....................................................................................................\hypara2.m
.....................................................................................................\normalize.m
.....................................................................................................\pso.m
.....................................................................................................\tpso1.m
.....................................................................................................\tpso2.m
.....................................................................................................\tpso3.m
.....................................................................................................\trainpso.m
.....................................................................................................\unwrapmat.m
.....................................................................................................\wrapmat.m