BP_Neural_Network-1.4
所属分类：人工智能/神经网络/深度学习
开发工具：Fortran
文件大小：400KB
下载次数：2
上传日期：2021-03-08 14:22:25
上 传 者：
谦善可掬
说明： 三层BP神经网络，可用于函数拟合，隐含层、输入层、输出层节点数可调整
(Three layer BP neural network can be used for function fitting, and the number of nodes in hidden layer, input layer and output layer can be adjusted)
文件列表:
BP_Neural_Network-1.4 (0, 2021-03-08)
BP_Neural_Network-1.4\BP_Neural_Network (0, 2021-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\BP_Neural_Network.u2d (284, 2021-01-18)
BP_Neural_Network-1.4\BP_Neural_Network\BP_Neural_Network.vfproj (4016, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\Code (0, 2021-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\Code\BP_Learning.f90 (3568, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\Code\BP_Learning_T.f90 (3858, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\Code\LHS.f90 (588, 2020-02-13)
BP_Neural_Network-1.4\BP_Neural_Network\Code\Main.f90 (1576, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\Code\Normalization.f90 (1492, 2020-03-15)
BP_Neural_Network-1.4\BP_Neural_Network\Code\Real_Function.f90 (327, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\Code\Transfer_function.f90 (1107, 2020-02-20)
BP_Neural_Network-1.4\BP_Neural_Network\Code\final_net.f90 (1234, 2020-02-20)
BP_Neural_Network-1.4\BP_Neural_Network\Code\input_initialize.f90 (2540, 2020-03-15)
BP_Neural_Network-1.4\BP_Neural_Network\Code\module.f90 (759, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\Code\output.f90 (2186, 2020-03-15)
BP_Neural_Network-1.4\BP_Neural_Network\input (0, 2021-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\input\GA_input.dat (203, 2015-08-30)
BP_Neural_Network-1.4\BP_Neural_Network\input\Kriging_input.dat (367, 2015-11-01)
BP_Neural_Network-1.4\BP_Neural_Network\midput (0, 2021-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\midput\LHS.dat (520, 2020-02-14)
BP_Neural_Network-1.4\BP_Neural_Network\output (0, 2021-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\output\LHS_response.dat (260, 2020-03-15)
BP_Neural_Network-1.4\BP_Neural_Network\output\Loss_function.dat (38000, 2020-03-15)
BP_Neural_Network-1.4\BP_Neural_Network\output\Real_figure.dat (740048, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\output\fitting_function.dat (5048, 2020-03-15)
BP_Neural_Network-1.4\BP_Neural_Network\output\noram_sample.dat (500, 2020-03-15)
BP_Neural_Network-1.4\BP_Neural_Network\vc100.pdb (53248, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\x64 (0, 2021-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\x64\Debug (0, 2021-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\x64\Debug\BP_Learning.obj (69196, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\x64\Debug\BP_Learning_T.obj (59922, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\x64\Debug\BP_Neural_Network.exe (165888, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\x64\Debug\BP_Neural_Network.exe.intermediate.manifest (381, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\x64\Debug\BP_Neural_Network.pdb (404480, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\x64\Debug\BuildLog.htm (4804, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\x64\Debug\LHS.obj (7007, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\x64\Debug\Main.obj (11190, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\x64\Debug\Normalization.obj (16603, 2020-03-08)
BP_Neural_Network-1.4\BP_Neural_Network\x64\Debug\Real_Function.obj (3352, 2020-03-08)
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