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《Journal of Hydroelectric Engineering》 2009-01
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Grey self-memory model based on BP neural network for annual runoff prediction

ZHANG Xiaowei,SHEN Bing,HUANG Lingmei(Key Lab of Northwest Water Resources and Environment Ecology,MOE at XAUT,Xi'an 710048)  
The key problem of improving the accuracy of runoff prediction is safficiently to dig the information included in the sample series.For the defect of the grey and grey self-memory model,on account of integrative prediction,the BP neural network is used to deal with the error existed in grey self-memory model,then the grey self-memory model based on BP neural network is developed.It is shown that the model has better prediction accuracy and may be used for annual runoff prediction.
【Fund】: 国家自然基金(50579063 50779052)
【CateGory Index】: P333.1
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【References】
Chinese Journal Full-text Database 1 Hits
1 Shi Biao1,Li Yuxia1,Yu Xinhua2,Niu Yanli1(1.Institute of Water Resources and Hydro-electric Engineering,Xi'an University of Technology,Xi'an 710048,China;2.Technical Institute of High Vocation,QingDao University of Science and Technology,Qingdao 261000,China);Long-term runoff forecast method based on dynamic adjustment particle swarm optimizer algorithm and Holt-Winters linear seasonal model[J];Transactions of the Chinese Society of Agricultural Engineering;2010-07
【Co-references】
Chinese Journal Full-text Database 9 Hits
1 YU Guo-rong1,YE Hui,2,XIA Zi-qiang3,ZHAO Xiao-yong4(1.Faculty of Electric Power Engineering,Kunming University of Science and Technology,Kunming 650051,China;2.Pulandian Water Resources Investigation and Design Institute of Dalian City,Pulandian 116200,China;3.State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University,Nanjing 210098,China;4.Yantai Water Conservancy Bureau,Yantai 264000,China);Application of projection pursuit auto regression model in predicting runoff of Yangtze River[J];Journal of Hohai University(Natural Sciences);2009-03
2 SHI Biao1,LI Yu-xia1,YU Xin-hua2,YAN Wang1(1.Institute of Water Resources and Hydro-electric Engineering,Xi'an University of Technology,Xi'an Shaanxi 710048,China;2.Technical Institute of High Vocation,Qingdao University of Science and Technology,Qingdao Shandong 261000,China);Short-term load forecast based on modified particle swarm optimizer and back propagation neural network model[J];Journal of Computer Applications;2009-04
3 RAN Du-kui1,2,LI Min3,WU Sheng1,4,XIE Jian-cang11.Key Lab of Northwest Water Resources and Environment Ecology of MOE,Xi’an University of Technology,Xi’an 710048,China 2.Hanjiang Hydropower Development Co.,Ltd,Danjiangkou,Hubei 442700,China 3.Northwest Investigation and Design Institute,Xi’an 710065,China 4.Northwest Electric Power Design Institute,Xi’an 710075,China;Application of ANN in study of hysteretic nature of factors influencing inflow runoff[J];Computer Engineering and Applications;2009-30
4 HUANG Guo-ru, RUI Xiao-fang (College of Water Resources and Environment, Hohai University, Nanjing 210098, China);Study advances in diagnosis of chaotic behaviour and its prediction for rainfall and streamflow time series in watershed[J];Advances In Water Science;2004-02
5 GAO Long-hua~1,2(1.Hohai University,Nanjing 210098,China;2.Pearl River Hydraulic Research Institute,Guangzhou 510611,China);Model of human driving force affecting the evolvement of runoff[J];Journal of Hydraulic Engineering;2006-09
6 QU Ya-ling, ZHOU Jian-zhong, LIU Fang, YANG Jun-jie, LI Ying-hai (College of Hydropower and Digital Engineering, Huazhong Science University, Wuhan 430074, China);Medium-and Long-Term Runoff Forecasting Based on Improved Elman Neural Network[J];Journal of China Hydrology;2006-01
7 TAO Feng-ling1,WU Sheng2,YU Sheng-cai1,XIAO Bo2(1.Qinghai University,Xining 810016,China;2.Xi'an University of Technology,Xi'an 710048,China);Longyangxia Runoff Forecasting Based on LS-SVM[J];Journal of China Hydrology;2008-04
8 GUO Chun,LI Zuo-yong,DANG Yuan (College of Resource and Environment,Chengdu University of Information and Technology,Chengdu 610225,China);Runoff prediction application of BP neural network model based on immune evolutionary algorithm[J];Water Resources Protection;2009-05
9 WANG Yong~1,ZHANG Gang~1,Pei-Chann Chang~2 (1.School of Management,Wuhan University of Science and Technology,Wuhan 430081,China;2.School of Information, Yuan Ze University,Taiwan 32026,China);Improved algorithm of evolutionary programming and its application research on optimization of ordering plan[J];Systems Engineering-Theory & Practice;2009-06
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