回归预测 | MATLAB实现BiLSTM双向长短期记忆神经网络多输入多输出预测

预测效果

基本介绍

MATLAB实现BiLSTM双向长短期记忆神经网络多输入多输出预测，数据为多输入多输出预测数据，输入10个特征，输出3个变量,程序乱码是由于版本不一致导致，可以用记事本打开复制到你的文件，运行环境MATLAB2018b及以上。命令窗口输出MAE和R2，可在下载区获取数据和程序内容。

程序设计

• 完整程序和数据下载方式(资源处直接下载)：MATLAB实现BiLSTM双向长短期记忆神经网络多输入多输出预测

%-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
layers = [ ...
    sequenceInputLayer(numFeatures)
   
    fullyConnectedLayer(numResponses)
    regressionLayer];
options = trainingOptions('adam', ...
    'MaxEpochs',250, ...
    'GradientThreshold',1, ...
    'InitialLearnRate',0.005, ...
    'LearnRateSchedule','piecewise', ...
    'LearnRateDropPeriod',125, ...
    'LearnRateDropFactor',0.2, ...
    'ExecutionEnvironment','cpu', ...
    'Verbose',0, ...
    'Plots','training-progress');
%-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------   
net = trainNetwork(XTrain,YTrain,layers,options);
dataTestStandardized = (dataTest - mu) / sig;
XTest = dataTestStandardized(1:end-1);
net = predictAndUpdateState(net,XTrain);
[net,YPred] = predictAndUpdateState(net,YTrain(end));
numTimeStepsTest = numel(XTest);
%-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

往期精彩

MATLAB实现RBF径向基神经网络多输入多输出预测
MATLAB实现BP神经网络多输入多输出预测
MATLAB实现DNN神经网络多输入多输出预测
MATLAB实现GRNN广义回归神经网络多输入多输出预测
MATLAB实现GRU门控循环单元多输入多输出

参考资料

[1] https://blog.csdn.net/kjm13182345320/article/details/116377961
[2] https://blog.csdn.net/kjm13182345320/article/details/127931217
[3] https://blog.csdn.net/kjm13182345320/article/details/127894261