基于典型小概率法-LSTM的大坝预警技术研究

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关键词：大坝安全；典型小概率法；LSTM；监测预警；三门峡水库中图分类号：TV87 文献标志码：A doi：10.3969/j.issn.1000-1379.2025.07.013引用格式：，，，等.基于典型小概率法-LSTM的大坝预警技术研究[J].人民黄河，2025，47（7）：78-83.

Research on Dam Early Warning Technology Based on Typical Small Probability Method-LSTM

LI Mingyang 1，2，3 ， DENG Yu 1，3 ， ZHANG Baosen 1，3 ， GUO Jinjun² （1.Yellw River Institute of Hydraulic Research， YRCC， Zhengzhou 450oO3，China; 2.School of Water Conservancy and Transportation， Zhengzhou University，Zhengzhou 45ooo1，China; 3.Research Center on Levee Safety and Disaster Prevention，MWR，Zhengzhou 45OOO3，China）

Abstract：Teperatioalsusofteameniaeseiitcallypacswatersuplsecuritdfdprevetofdowsai iesalong eYelowRiverHowever，onventioaloitoigapproacsrelingonssortwoksandmanualbservatiossuferfroin adequatereal-tpefoaedisuentpreTdsselatios，issdeveedtegadrld elincorporatingulti-soucedataanddamicesponsemechanisms.Themethodologinvoledcalulatingwaingtresholdsforrialprameters（e.g，damdisplacementandsepagepresure）usingtheTypicalSmallProbabilityMethod，coupledwithanLSTM-basedpredic tionmodelforficient waringtoughthresholdcomparisonValidationusingtheSanmenxiaReservoircasedemonstratesthemodel’ssuperior predictive accuracy compared to traditional methods.

KeyWords：dam safety；typical smallprobabilitymethod;LSTM；monitoring and early warning；Sanmenxia Reservoir

0 引言

黄河三门峡水库作为黄河流域防洪与水资源调配的重要枢纽，其安全运行直接影响下游城市供水与生态稳定，不仅是黄河流域水资源调配和防洪减灾的枢纽工程，也是保障周边地区经济社会稳定发展的生命线[1-3]。（剩余8227字）