CNN-LSTM寿命预测MATLAB代码
时间: 2023-07-12 12:16:27 浏览: 82
以下是使用CNN-LSTM预测寿命的MATLAB代码示例:
首先,加载数据集并进行预处理:
```matlab
load('data.mat'); % 加载数据集
X = data(:, 1:end-1); % 输入数据
Y = data(:, end); % 输出数据
% 将数据集分为训练集和测试集
train_ratio = 0.8; % 训练集比例
train_size = floor(train_ratio * size(X, 1));
XTrain = X(1:train_size,:);
YTrain = Y(1:train_size,:);
XTest = X(train_size+1:end,:);
YTest = Y(train_size+1:end,:);
% 标准化输入数据
mu = mean(XTrain);
sigma = std(XTrain);
XTrain = (XTrain - mu) ./ sigma;
XTest = (XTest - mu) ./ sigma;
% 将数据转换为序列形式
num_features = size(X, 2);
seq_length = 10; % 序列长度
XTrain_seq = cell(size(XTrain,1)-seq_length+1,1);
YTrain_seq = cell(size(XTrain,1)-seq_length+1,1);
for i = 1:size(XTrain,1)-seq_length+1
XTrain_seq{i} = XTrain(i:i+seq_length-1,:)';
YTrain_seq{i} = YTrain(i+seq_length-1);
end
XTest_seq = cell(size(XTest,1)-seq_length+1,1);
YTest_seq = cell(size(XTest,1)-seq_length+1,1);
for i = 1:size(XTest,1)-seq_length+1
XTest_seq{i} = XTest(i:i+seq_length-1,:)';
YTest_seq{i} = YTest(i+seq_length-1);
end
% 将数据集转换为 dlarray 格式
XTrain_seq = dlarray(cat(3, XTrain_seq{:}));
YTrain_seq = cat(1, YTrain_seq{:});
XTest_seq = dlarray(cat(3, XTest_seq{:}));
YTest_seq = cat(1, YTest_seq{:});
```
接下来,定义CNN-LSTM模型:
```matlab
inputSize = num_features;
numHiddenUnits = 64;
numClasses = 1;
layers = [ ...
sequenceInputLayer(inputSize)
convolution2dLayer([1 3],16,'Padding','same')
batchNormalizationLayer
reluLayer
sequenceFoldingLayer('Name','fold')
lstmLayer(numHiddenUnits,'OutputMode','last')
dropoutLayer(0.5)
fullyConnectedLayer(numClasses)
regressionLayer];
options = trainingOptions('adam', ...
'MaxEpochs',30, ...
'MiniBatchSize',128, ...
'Shuffle','never', ...
'ValidationData',{XTest_seq,YTest_seq}, ...
'ValidationFrequency',10, ...
'GradientThreshold',1, ...
'Verbose',false, ...
'Plots','training-progress');
model = trainNetwork(XTrain_seq,YTrain_seq,layers,options);
```
最后,进行预测并计算误差:
```matlab
YPred = predict(model,XTest_seq);
YPred = YPred{end};
YTest = gather(YTest_seq);
% 反标准化输出数据
YPred = YPred .* std(YTrain) + mean(YTrain);
YTest = YTest .* std(YTrain) + mean(YTrain);
% 计算均方误差
mse = mean((YPred - YTest).^2);
disp(['Test MSE: ',num2str(mse)]);
```
这是一个简单的CNN-LSTM寿命预测MATLAB代码示例。需要根据实际情况进行适当修改和调整。