Shenjinwangluo

代码说明：

  （1） 本系统用到四种神经网络对漏电嫌疑系数进行预测，分别是BP神经网络、RBF神经网络、GRNN神经网络、Elman神经网络，通过对神经网络结构参数的设置和调试，可以得到很好的预测效果，实际值和预测值之间的误差能达到5 以内。 （2） 本系统使用matlab做GUI界面，在界面上就可以分别对这四种神经网络的结构参数进行设置，从而可以调整神经网络的结构，达到较好的预测精度。 ((1) The system used four neural network to predict the suspected leakage coefficient, respectively, the BP neural network, RBF neural network, GRNN neural network, Elman neural network, the neural network structure parameter setting and commissioning, can get very good prediction, between the actual and predicted values ​ ​ of error of less than 5 . (2) the use matlab to do the GUI interface, the interface can each of these four neural network structure parameters set, the structure of the neural network, which can be adjusted to achieve better prediction accuracy.)

文件列表：

yuce
....\fanloudian.xls,53760,2012-05-09
....\hs_err_pid1256.log,17456,2012-05-09
....\hs_err_pid1412.log,16792,2012-05-05
....\hs_err_pid3352.log,17421,2012-05-09
....\hs_err_pid3624.log,16913,2012-05-05
....\hs_err_pid3788.log,17426,2012-05-05
....\hs_err_pid4148.log,16619,2012-05-16
....\hs_err_pid640.log,17054,2012-05-05
....\jianyanshuju.m,149,2012-05-09
....\jiemian.asv,14951,2012-05-14
....\jiemian.fig,5400,2012-05-16
....\jiemian.m,14942,2012-05-14
....\RBFyuce.m,262,2012-05-05
....\xunlianmubiao.xlsx,12671,2012-05-09
....\xunlianyanben.xlsx,25537,2012-05-09
....\yuce.asv,434,2012-05-09
....\yuce.m,434,2012-05-09
....\yucemubiao.xlsx,10313,2012-05-09
....\yucetest.xlsx,11657,2012-05-08
....\反漏窃电样本.xls,56832,2012-05-04
....\精度图.docx,138527,2012-05-09