南京大学学报：自然科学版2012，Vol.48Issue(6)：736-745,10.
基于小波消噪与秩次集对分析的水文时间序列预测模型
Hydrologic temporal series prediction model based on wavelet de-noising and rank and set-pair analysis
摘要
Abstract
Observations of hydrologic series are always with tendency, periodicity, randomness and other characteristics. Especially under large-scale conditions, there are many problems in the hydrologic series prediction, such as single construction method and without consideration of the noise. Therefore, a hydrologic series prediction model (WD-RSPA model) is developed on the combination of wavelet de-noise(WD)method and rank and set-pair analysis(RSPA), which takes advantage of multi scale analysis and noise reduction in wavelet analysis and clear concept, simple calculation, and overcomes the subjectivity to certain the standard of set elements in RSPA. The WD-RSPA model is applied to predict the annual runoff of Huayuankou Station and the annual precipitation of Zhengzhou Station. The prediction results by WD-RSPA model are compared with results of traditional RSPA model, AR model and BP neural network model. It indicates that, with appropriate de-noising wavelet function and pair dimension, WDRSPA model can avoid the impact of noise efficiently, the concept to establish WD-RSPA model is clear, the computation is simper and the accuracy of prediction results is higher. Consequently, the applicability,dependability and advantage of WD-RSPA model is validated.关键词
水文时间序列预测/小波消噪/秩次集对分析Key words
hydrologic series prediction/wavelet de-noise/rank and set-pair analysis分类
数理科学引用本文复制引用
何菡丹,王栋..基于小波消噪与秩次集对分析的水文时间序列预测模型[J].南京大学学报：自然科学版,2012,48(6):736-745,10.基金项目
基金项目：国家自然科学基金 （）
南京大学青年骨干教师和优秀中青年学科带头人培养计划 （）
