摘要
针对传统降水预测方式存在的不足,提出一种基于协整理论的极限学习机模型,该模型主要利用协整理论将相关序列信息引入,运用极限学习机(ELM)刻画非线性映射关系,并将该模型应用于皖南地区季度平均降水预测中。结果表明,该模型预测结果合理,且具有更佳的表现。
Aiming at the drawbacks of the traditional precipitation prediction method,this paper proposed an extreme learning machine model based on cointegration theory.Co-integration was introduced to add relevant information of the series in extreme learning machine.Extreme learning machine was employed to depict the nonlinear relationship of the series.The model was applied to predict seasonal average precipitation in Southern Anhui Region.The results show that the proposed model is reasonable and it has good performace.
出处
《水电能源科学》
北大核心
2017年第9期1-3,12,共4页
Water Resources and Power
基金
国家自然科学基金项目(41571016)
关键词
降水
预测
协整理论
极限学习机
皖南地区
precipitation
prediction
cointegration theory
ELM
Southern Anhui Region
