基于SPEI指数的河北省夏秋两季干旱预测研究  

Prediction of Drought in Summer and Autumn in Hebei Province Based on SPEI Index

作　　者：张冉 王海兴 张照娜 陆禹阔 史东旭 许超前 贾悦 Zhang Ran;Wang Haixing;Zhang Zhaona;Lu Yukuo;Shi Dongxu;Xu Chaoqian;Jia Yue(Hebei University of Water Resource and Electric Engineering&Remote Sensing and Smart Water Innovation Center,Cangzhou,China)

机构地区：[1]河北水利电力学院遥感与智慧水利创新中心,河北沧州

出　　处：《科学技术创新》2024年第8期70-73,共4页Scientific and Technological Innovation

基　　金：河北省高等学校科学技术研究项目资助(QN2021227);2021年河北水利电力学院河北省高等学校基本科研业务费研究项目(SYKY2132)。

摘　　要：为获得河北省夏、秋两季干旱预测模型,本文以标准化降雨蒸散指数(SPEI)为基础,基于极限学习机模型(ELM),采用麻雀搜索算法(SSA)、蜂群算法(ABC)、蝙蝠算法(BA)、粒子群算法(PSO)、遗传算法(GA)共5种优化算法构建了优化ELM模型用于建立区域SPEI指数估算模型,结果表面:SSA-ELM模型在所有模型中精度最高,同时可移植性较好,可作为河北省夏、秋两季的干旱预测模型使用。In order to obtain drought prediction models for summer and autumn in Hebei Province,in this paper,based on standardized rainfall Evapotranspiration Index(SPEI) and extreme learning Machine model(ELM),five optimization algorithms,namely sparrow search algorithm(SSA),bee colony algorithm(ABC),bat algorithm(BA),particle swarm optimization algorithm(PSO) and genetic algorithm(GA),were used to construct an optimized ELM model for establishing a regional SPEI index estimation model.The results showed that:SSA-ELM model had the highest precision and good portability among all models,and can be used as a drought prediction model in summer and autumn of Hebei Province.

关 键 词：河北省 标准化降雨蒸散指数 极限学习机模型 麻雀搜索算法 模型可移植性 

分 类 号：P426.616[天文地球—大气科学及气象学]