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基于灰色关联与SVM的蒸发量季节性预测 被引量:4

Seasonal Prediction of Evaporation Based on Gray Correlation and SVM
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摘要 为正确认识蒸发量与气象因子之间的关系,以山西太原气象站为例,应用灰色关联分析选择关联度较高的气象因子,利用Matlab软件构建以该站2010~2016年日气象数据作为训练样本、分5个时段建立26个气象因子组合下的130个蒸发量SVM预测模型,并以2017年日气象数据作为验证样本,对模型模拟结果进行验证。结果表明,季节性蒸发量预测模型模拟精度高于全年蒸发量预测模型,且气象因子组合对模型模拟效果具有重大影响,在太原地区最佳季节性模型春、夏、秋、冬四季所对应的因子组合及数量均不同,模型预测R2值分别为0.78、0.53、0.53、0.51,RMSE值分别为0.83、1.42、1.16、1.31,预测结果较好。 To understand the relationship between evaporation and meteorological factors,this article chose Taiyuan station of Shanxi as the research object.The grey relation analysis was used to choose high correlation factors,and Matlab software was used to establish 130 evaporation SVM prediction model under 26 meteorological factors combination with five time intervals.The site daily meteorological data from 2010 to 2016 was taken as the training sample.The daily meteorological data in 2017 was used as the validation samples to test the simulation results of the model.The results show that the prediction model accuracy of seasonal evaporation capacity is higher than the annual prediction model,and the meteorological factors combination has a significant impact on the simulation effect of the model.In Taiyuan region,factor combination and number for the best spring,summer,autumn,winter seasonal model are different.The R2 values of prediction models were 0.78,0.53,0.53 and 0.51,RMSEvalues were 0.83,1.42,1.16 and 1.31,respectively.The effect of prediction model is good.
作者 牛秀岭 NIU Xiu-ling(Shanxi Water Industry Jiaokou Water Supply Development and Construction Management Co.,LTD.,Taiyuan 030002,China)
出处 《水电能源科学》 北大核心 2019年第2期18-21,共4页 Water Resources and Power
基金 国家自然科学基金青年基金项目(41702263)
关键词 灰色关联 SVM模型 蒸发量 因子组合 季节性模型 gray correlation SVM model evaporation factors combination seasonal model
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