基于改進CBR算法特征權重分配的震后應急物資需求預測方法

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中圖分類號：TP391 文獻標識碼：A 文章編號：2096-4706（2025）07-0133-06

Abstract：Inorder toimprove theaccuracyofpost-earthquake emergencymaterial demandforecasting，this paper proposes afeatureweightllocationmethodbasedonimprovedCase-BasedReasoning（CBR）algorithm，andconstructsapost-earthquake emergencymaterial demand forecasting modelbasedonsafetystock theory.The model isbasedonseven earthquakedisaster indicatorssuchasagntude，focaldepth，artquakeocrecetime，populationdensityumberofousecollaps，eisic fortificationintensityandseismicintensity.Itcanacuratelyforecastthedemandforvarioustypesofemergencymaterialsafter theearthquake.The experimentalresults show thatthe MeanRelative Errorof the forcast valueobtained bythe forecasting model optimized bygame theory-improved geneticalgorithm（SAGA）and Analytic Hierarchy Process （AHP）algorithmare 89 . 5 7 % and 8 7 . 5 1 % lower than that obtained by GA algorithm optimization and SAGA algorithm optimization，respectively. This showsthat the modelcan providestrong technicalsupport for theeffcientallocationofpost-earthquake emergency materials.

Keywords： post-earthquake emergency material; demand forecasting; game theory; SAGA algorithm; Case-Based Reasoning algorithm

0 引言

中國位于歐亞地震帶和環(huán)太平洋地震帶之間，地震災害的頻繁發(fā)生嚴重威脅著國家的社會建設、經濟發(fā)展和人民生命安全[。（剩余7281字）