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及文章作者：机器学习之心
摘要：TSOA-TCN-Attention凌日算法优化时序卷积神经网络多变量多步预测
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基本介绍
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运行效果
完整代码可扫描二维码获取：
或电脑浏览器打开链接：https://mbd.pub/o/bread/mbd-Z5WWmZtp
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%% 清空环境变量warning off % 关闭报警信息close all % 关闭开启的图窗clear % 清空变量clc % 清空命令行methodsfunction layer = spatialDropoutLayer(dropoutFactor,NameValueArgs)% layer = spatialDropoutLayer creates a spatial dropout layer% with dropout factor 0.02;%% layer = spatialDropoutLayer(dropoutProb) creates a spatial% dropout layer with the specified probability.%% layer = spatialDropoutLayer(__,Name=name) also specifies the% layer name using any of the previous syntaxes.% Parse input arguments.argumentsdropoutFactor = 0.02;NameValueArgs.Name = ""endname = NameValueArgs.Name;% Set layer properties.layer.Name = name;layer.Description = "Spatial dropout with factor " + dropoutFactor;layer.Type = "Spatial Dropout";layer.DropoutFactor = dropoutFactor;endfunction Z = predict(layer, X)% Forward input data through the layer at prediction time and% output the result.%% Inputs:% layer - Layer to forward propagate through% X - Input data% Output:% Z - Output of layer forward function% At prediction time, the output is unchanged.Z = X;endfunction Z = forward(layer, X)
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嗯，细心的你会发现：https://mbd.pub/o/slowtrain/work
博客专家认证，机器学习领域创作者，2023博客之星TOP50，主做机器学习和深度学习时序、回归、分类、聚类和降维等程序设计和案例分析。
其他多变量多步代码：
SCI一区级 | Matlab实现GWO-CNN-LSTM-selfAttention多变量多步时间序列预测
SCI一区级 | Matlab实现EVO-CNN-LSTM-Mutilhead-Attention多变量多步时间序列预测
SCI一区级 | Matlab实现EVO-CNN-BiLSTM-Mutilhead-Attention多变量多步时间序列预测
