CNN岩爆预测模型matlab
时间: 2023-07-28 18:07:35 浏览: 57
以下是一个使用MATLAB实现CNN岩爆预测模型的示例代码,其中包括数据预处理、模型定义、训练和测试等步骤:
```matlab
% 读取数据
data = load('rock_explosion_data.mat');
X_train = data.X_train;
Y_train = data.Y_train;
X_test = data.X_test;
Y_test = data.Y_test;
% 数据预处理
X_train = reshape(X_train, [100, 100, 1, size(X_train, 1)]);
X_test = reshape(X_test, [100, 100, 1, size(X_test, 1)]);
Y_train = double(Y_train);
Y_test = double(Y_test);
% 定义卷积神经网络模型
layers = [
imageInputLayer([100 100 1])
convolution2dLayer(3, 16, 'Padding', 'same', 'Activation', 'relu')
maxPooling2dLayer(2, 'Stride', 2)
convolution2dLayer(3, 32, 'Padding', 'same', 'Activation', 'relu')
maxPooling2dLayer(2, 'Stride', 2)
convolution2dLayer(3, 64, 'Padding', 'same', 'Activation', 'relu')
maxPooling2dLayer(2, 'Stride', 2)
fullyConnectedLayer(128, 'Activation', 'relu')
fullyConnectedLayer(1, 'Activation', 'sigmoid')
regressionLayer];
% 设置训练参数
options = trainingOptions('adam', ...
'MaxEpochs', 20, ...
'MiniBatchSize', 128, ...
'Shuffle', 'every-epoch', ...
'Plots', 'training-progress');
% 训练模型
net = trainNetwork(X_train, Y_train, layers, options);
% 测试模型
YPred = predict(net, X_test);
rmse = sqrt(mean((YPred - Y_test).^2));
disp(['RMSE: ', num2str(rmse)]);
```
需要注意的是,以上示例代码仅供参考,具体实现可能需要进行一些调整和优化。同时,还需要根据实际数据进行预处理和特征提取等操作。