基于自编码器的电力负荷预测

Question

请问怎么样用Matlab来实现基于自编码器对一个特定电力负荷数据集的预测

Answer 1

load data.mat
[numPoints, numFeatures] = size(data);

layers = [
    % 特征输入层
    featureInputLayer(numFeatures);
    % 全连接层-1
    fullyConnectedLayer(15)
    reluLayer
    % 全连接层-2
    fullyConnectedLayer(2)
    reluLayer
    % 全连接层-3
    fullyConnectedLayer(15)
    reluLayer
    % 回归输出层
    fullyConnectedLayer(numFeatures)
    regressionLayer];

% 训练参数设置
options = trainingOptions('adam', ...
    'ExecutionEnvironment', 'auto', ...
    'MiniBatchSize', 50, ...
    'MaxEpochs', 200, ...
    'Shuffle', 'every-epoch', ...
    'Plots', 'training-progress', ...
    'Verbose', false);


net = trainNetwork(data, data, layers, options);

% 可视化网络结构
analyzeNetwork(net)


layer = 'relu_2';
featuresTrain = activations(net, data, layer, 'OutputAs', 'rows');

figure
scasize = 32;
scatter(featuresTrain(:, 1), featuresTrain(:, 2), scasize,...
    'MarkerEdgeColor', 'k',...
    'MarkerFaceColor', [0 0.4470 0.7410])
title('特征提取结果')

% 数据重构
dataPred = predict(net, data);

figure
scatter3(dataPred(:, 1), dataPred(:, 2), dataPred(:, 3), scasize,...
    'MarkerEdgeColor', 'k',...
    'MarkerFaceColor', [0 0.4470 0.7410])
hold on
scatter3(data(:, 1), data(:, 2), data(:, 3), scasize,...
    'MarkerEdgeColor', 'k',...
    'MarkerFaceColor', [0.6350 0.0780 0.1840])
legend({'重构数据', '原始数据'})

可以参考