神经网络中的BP算法和Elman算法

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clear all;%输入数据P = [0.4413 0.4707 0.6953 0.8133 0.4379 0.4677 0.6981 0.8002 0.4517 0.4725 0.7006 0.8201;     0.4379 0.4677 0.6981 0.8002 0.4517 0.4725 0.7006 0.8201 0.4557 0.4790 0.7019 0.8211;     0.4517 0.4725 0.7006 0.8201 0.4557 0.4790 0.7019 0.8211 0.4601 0.4911 0.7101 0.8298]';%输出数据T = [0.4557 0.4790 0.7019 0.8211;     0.4601 0.4911 0.7101 0.8298;     0.4612 0.4845 0.7188 0.8312]';%创建神经网络net_1 = newff(minmax(P),[12,4],{'tansig','purelin'},'traingdm');%设置训练参数net_1.trainParam.show = 50;net_1.trainParam.lr = 0.05;net_1.trainParam.mc = 0.9;net_1.trainParam.epochs = 10000;net_1.trainParam.goal = 1e-3;%训练网络[net_1,tr] = train(net_1,P,T);%使用训练好的网络，自定义输入A = sim(net_1,P);%理想输出与训练输出的结果进行比较E = T - A;%计算误差MSE = mse(E)%第二组验证P1 = [0.4557 0.4790 0.7019 0.8211 0.4601 0.4911 0.7101 0.8298 0.4612 0.4845 0.7188 0.8312]';T1 = [0.4615 0.4891 0.7201 0.8330]';A1 = sim(net_1,P1);E1 = T1 - A1;MSE1 = mse(E1)

%Elman神经网络预测空调负荷（仿BP）clear all;%输入数据P = [0.4413 0.4707 0.6953 0.8133 0.4379 0.4677 0.6981 0.8002 0.4517 0.4725 0.7006 0.8201;     0.4379 0.4677 0.6981 0.8002 0.4517 0.4725 0.7006 0.8201 0.4557 0.4790 0.7019 0.8211;     0.4517 0.4725 0.7006 0.8201 0.4557 0.4790 0.7019 0.8211 0.4601 0.4911 0.7101 0.8298]';%输出数据T = [0.4557 0.4790 0.7019 0.8211;     0.4601 0.4911 0.7101 0.8298;     0.4612 0.4845 0.7188 0.8312]';%创建神经网络net_1 = newelm(minmax(P),[12,4],{'tansig','purelin'},'traingdm');%设置训练参数net_1.trainParam.show = 50;net_1.trainParam.lr = 0.05;net_1.trainParam.mc = 0.9;net_1.trainParam.epochs = 10000;net_1.trainParam.goal = 1e-3;%训练网络[net_1,tr] = train(net_1,P,T);%第1组验证%使用训练好的网络，自定义输入A1 = sim(net_1,P);%理想输出与训练输出的结果进行比较E1 = T - A1;%计算误差MSE = mse(E1)%第2组验证（从输入样本中抽取一组输入P2，对应的输出样本中抽出T2）P2 = [0.4517 0.4725 0.7006 0.8201 0.4557 0.4790 0.7019 0.8211 0.4601 0.4911 0.7101 0.8298]';T2 = [0.4612 0.4845 0.7188 0.8312]';A2 = sim(net_1,P2);E2 = T2 - A2;MSE1 = mse(E2)%第3组验证 (本组输入P3和输出T3不是从训练样本中取得的，得到的误差有点大)P3 = [0.4557 0.4790 0.7019 0.8211 0.4601 0.4911 0.7101 0.8298 0.4612 0.4845 0.7188 0.8312]';T3 = [0.4615 0.4891 0.7201 0.8330]';A3 = sim(net_1,P3);E3 = T3 - A3;MSE1 = mse(E3)

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