基于TimeGAN增強(qiáng)的CNN-LSTM模型在盾構(gòu)掘進(jìn)地表沉降中的預(yù)測研究
摘要: 為更準(zhǔn)確地預(yù)測小數(shù)據(jù)量下盾構(gòu)法施工造成的地表沉降,提出基于Time GAN(time series generative adversarial networks,時(shí)間序列生成對抗網(wǎng)絡(luò))增強(qiáng)的CNN(convolutional neural networks,卷積神經(jīng)網(wǎng)絡(luò))-LSTM(long short-term memory,長短期記憶網(wǎng)絡(luò))盾構(gòu)掘進(jìn)地表沉降預(yù)測模型,并依托... (共10頁)
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