Dam deformation prediction method, system and equipment and storage medium

The invention provides a dam deformation prediction method, system and device and a storage medium, and relates to the field of dam safety monitoring. The method comprises the following steps: obtaining dam monitoring data, wherein the dam monitoring data comprises a target deformation amount and a...

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Hauptverfasser: TAN YONG, CHI HONGYOU, TIAN YALING, HU LEI, HONG LIYANG, QIN PENG, LI BO, YANG SHENGMEI, HU CHAO, LIU KANG, WEI XUBEI, ZHANG QILING, CHEN LI, GAO XIAOFENG, GAN XIAOQING
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creator TAN YONG
CHI HONGYOU
TIAN YALING
HU LEI
HONG LIYANG
QIN PENG
LI BO
YANG SHENGMEI
HU CHAO
LIU KANG
WEI XUBEI
ZHANG QILING
CHEN LI
GAO XIAOFENG
GAN XIAOQING
description The invention provides a dam deformation prediction method, system and device and a storage medium, and relates to the field of dam safety monitoring. The method comprises the following steps: obtaining dam monitoring data, wherein the dam monitoring data comprises a target deformation amount and a plurality of input characteristics; performing data mining on the dam monitoring data based on a Lasso regression algorithm to obtain a feature weight, corresponding to the target deformation, of each input feature; sorting and/or screening the plurality of input features based on the feature weights, corresponding to the target deformation, of the input features to obtain optimized input features; and the optimized input features are sent to a preset encoder part of the LSTM network, and a decoder part of the LSTM network introduces an attention mechanism to perform time sequence prediction on the prediction target deformation based on the output of the encoder and the result of the attention mechanism. According
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The method comprises the following steps: obtaining dam monitoring data, wherein the dam monitoring data comprises a target deformation amount and a plurality of input characteristics; performing data mining on the dam monitoring data based on a Lasso regression algorithm to obtain a feature weight, corresponding to the target deformation, of each input feature; sorting and/or screening the plurality of input features based on the feature weights, corresponding to the target deformation, of the input features to obtain optimized input features; and the optimized input features are sent to a preset encoder part of the LSTM network, and a decoder part of the LSTM network introduces an attention mechanism to perform time sequence prediction on the prediction target deformation based on the output of the encoder and the result of the attention mechanism. 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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
MEASURING
MEASURING ANGLES
MEASURING AREAS
MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
MEASURING LENGTH, THICKNESS OR SIMILAR LINEARDIMENSIONS
PHYSICS
TESTING
title Dam deformation prediction method, system and equipment and storage medium
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