基于优化ELM模型的河北省蒸发预测模型构建  

Construction of Evaporation Prediction Model in Hebei Province Based on Optimized ELM Model

作　　者：张勇顺 单长河 贾悦 张冉 黄东风 Zhang Yongshun;Shan Changhe;Jia Yue;Zhang Ran;Huang Dongfeng(South Canal River Affairs Center of Hebei Province,Cangzhou,China;Hebei University of Water Resource and Electric Engineering&Remote Sensing and Smart Water Innovation Center,Cangzhou,China;Botou Grand Canal Water Conservancy Construction Co.,Ltd.,Cangzhou,China)

机构地区：[1]河北省南运河河务中心,河北沧州 [2]河北水利电力学院遥感与智慧水利创新中心,河北沧州 [3]泊头市大运河水利建设有限公司,河北沧州

出　　处：《科学技术创新》2023年第7期61-64,共4页Scientific and Technological Innovation

基　　金：河北省高等学校科学技术研究项目(QN2021227);河北省水利科研与推广计划项目(2020-64);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：为找到河北省最优水面蒸发(Epan)估算模型,本研究以Penpan模型计算结果为标准值,以极限学习机模型(ELM)为基础,基于麻雀搜索算法构建了一种优化ELM模型,仅以温度资料为输入项,构建了河北省Epan估算模型,结果表明:SSA-ELM模型在估算Epan日值和月值中均表现出了较高的精度,同时该模型可移植性较高,可作为河北省Epan估算的推荐模型使用。To find the best water surface evaporation(Epan)estimation model in Hebei Province,in this paper,the optimized ELM models were constructed based on Sparrow Search Algorithm(SSA).We compared the accuracy of the models based on the results of Penpan model as the standard value.Estimating model of Epan in Hebei Province is constructed based on temperature data.The results showed that:SSA-ELM model showed high accuracy in estimating Epan daily and monthly values,and had high portability,which can be used as the recommended model for Epan estimation in Hebei Province.

关 键 词：河北省 水面蒸发 极限学习机模型 麻雀搜索算法 模型可移植性 

分 类 号：P332.2[天文地球—水文科学]