黄河径流长期演化模式与EMD灰色自记忆模型  

Evolution modes and EMD gray self-memory model of the Yellow River water resources

作　　者：吕继强[1] 沈冰[1] 邵年华[1] 董克鹏 李抗彬[1] 

机构地区：[1]西安理工大学西北水资源与环境生态教育部重点实验室,西安710048 [2]新疆和田水文水资源勘测局,新疆和田848000

出　　处：《水力发电学报》2012年第3期25-30,共6页Journal of Hydroelectric Engineering

基　　金：国家自然科学基金重点项目(50939004);国家自然科学基金项目(50779052)

摘　　要：为了研究径流的长期演化模式及自记忆特征,采用自相关函数确定重构序列的回溯阶数,并构建基于经验模态函数(EMD)分解的灰色自记忆GM(1,N)预测模型。分析回溯阶和自相关函数之间关系,进一步阐明自记忆原理在水文领域应用的合理性。结果表明,黄河花园口86年天然径流序列存在长期演化的自记忆特征,演化模式可由7个内在本征模态函数(IMF)和趋势项组成;受流域水资源开发及气候变化因素影响,1965年后,径流演化模式发生变化,出现周期衰减现象;回溯阶与时间序列自相关函数变化相对应,序列平稳化后,依据自相关函数确定回溯阶数,可提高自记忆模型预测精度。To better understand the evolution modes and self-memory characteristics of the Yellow River annual runoff,a gray self-memory prediction model is developed by using empirical mode decomposition theory.A auto-correlation function is adopted to define the backdate orders of this model to improve its accuracy.The results show that the runoff series at Huayuankou gauge can be decomposed into seven intrinsic mode functions（IMF） and a tendency function.Since 1965 the evolution modes and periodicity of runoff series has changed under the influences by water resources development and climate change in this river basin.

关 键 词：水文学及水资源 经验模态函数 EMD自记忆模型 黄河 

分 类 号：TV121[水利工程—水文学及水资源]