基于LSTM-Attention组合模型的黄金价格预测

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中图分类号：TP391.4 文献标识码：A 文章编号：2096-4706（2025）11-0144-07

Gold Price Prediction Based onLSTM-Attention Combination Model

WU Junping，LIU Jihua，QIN Yulu （Businesschool，HubeiUniversity，Wuhan43oo62，China）

Abstract： This paper explores efective methods for predicting gold prices，and proposes three modeling strategies includingstandaloneLong Short-Term Memory（LSTM）networks，Atentionbased models，andLSTM-Atentioncombiation model.Through empiricalanalysis，itsystematicallycompares the performanceofthesethree models ingold price prediction， withafocusonevaluating their predictiveaccuracy.Theexperimentalresults indicatethattheLSTM-Attentioncombination model significantlyoutperforms the standaloneLSTMandAtentionmodelsintermsofpredictionaccuracy，demonstratinga morecomprehensiveabilitytocapture thedynamic featuresofpricefuctuations.This modelnotonlyshowcases thepotentialof effective integrationofLSTandAentonechaismintiesriespreditionutalsoprovidesapracticaltoolforfcial decision-making，offering valuable references for investors in a volatile market environment.

Keywords： gold; LSTM; price prediction; Attention

0 引言

黄金价格作为全球金融市场的重要指标之一，不仅反映了经济形势的变化，还对投资者和政策制定者的决策产生深远影响。（剩余10895字）