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1、1.BP网络实验过程1.Matlab程序如下：clear;p=[1739.94,373.3,1756.77,864.45,222.85,877.88,1803.58,2352.12,401.3,363.34,1571.17,104.8,499.85,2297.28,2092.62,1418.79,1845.59,2205.36,2949.16,1692.62,1680.67,2802.88,172.78,2063.54,1449.58,1651.52,341.59,291.02,237.63;1675.15,3087.05,
2、1652,1647.31,3059.54,2031.66,1583.12,2557.04,3259.94,3477.95,1731.04,3389.83,3305.75,3340.14,3177.21,1775.89,1918.81,3243.74,3244.44,1867.5,1575.78,3017.11,3084.49,3199.76,1641.58,1713.28,3076.62,3095.68,3077.78;2395.96,2429.47,1514.98,2665.9,2002.33,3071.18,2163.0
3、5,1411.53,2150.98,2462.86,1735.33,2421.83,2196.22,535.62,584.32,2772.9,2226.49,1202.69,662.42,2108.97,1725.1,1984.98,2328.65,1257.21,3405.12,1570.38,2438.63,2088.95,2251.96];t=[01001000110110000000001000111;10100010001000001001100001000;0000000100000110011001010000
4、0;00010100000000010000000010000];net=newff(minmax(p),[12,4],{'tansig','logsig'},'trainlm');net.trainParam.epochs=400;net.trainParam.goal=0.01;net=train(net,p,t);p_test=[1702.81877.93867.811831.49460.692374.982271.891783.64198.831494.631597.031598.931243.132336.3135
5、42144.47426.311507.13343.072201.942232.431580.11962.41495.181125.1724.221269.071802.071817.361860.45;1639.791860.962334.681713.113274.773346.983482.971597.993250.452072.591921.521921.081814.072640.263300.122501.623105.291556.893271.723196.223077.871752.071594.97195
6、7.441594.393447.311910.721725.811927.41782.88;2068.741975.32535.11604.682172.99975.31946.72261.312445.082550.512126.761623.333441.071599.632373.61591.512057.81954.512036.94935.531298.872463.041835.953498.022937.732145.012701.971966.352328.791875.83];y=sim(net,p_tes
7、t);运行上述程序代码后，可以得到网络的训练结果：TRAINLM,Epoch0/400,MSE0./0.01,Gradient12110.8/1e-010TRAINLM,Epoch25/400,MSE0./0.01,Gradient3.47072/1e-010TRAINLM,Epoch50/400,MSE0./0.01,Gradient42.9197/1e-010TRAINLM,Epoch75/400,MSE0./0.01,Gradient4.53362/1e-010TRAINLM,Epoch100/400,MSE0./0.
8、01,Gradient1.61972/1e-010TRAINLM,Epoch125/400,MSE0./0.01,Gradient4.97853/1e-010TRAINLM,Epoch150/400,MSE0./0.01,Gradient1.97426/1e-010TRAINLM,Epoc
