Title :
Study on GM (1, N) self-memory and neural network combined model for evaporation forecasting
Author :
Duan, Haini ; Shen, Bing ; Mo, Shuhong ; Han, Haijun
Author_Institution :
Key Lab. of North-West Water Resources & Ecology Environ. of Educ. Minist., Xi´´an Univ. of Technol., Xi´´an, China
Abstract :
Hydrological elements forecasting model has been improved continuously. The variation of hydrological elements has uncertainty, in order to explain the mechanism, we need to consider more factors related. In this study, gray model (GM (1, N)) self-memory model was established to consider more related factors, and then it was combined with back-propagation (BP) neural network model. Based on this combined, the annual potential evaporation in Moyu County, Xinjiang Uygur Autonomous Region, was forecasted with satisfactory result.
Keywords :
backpropagation; evaporation; grey systems; hydrological techniques; neural nets; backpropagation neural network model; evaporation forecasting; gray model; hydrological element forecasting model; neural network combined model; self-memory model; Artificial neural networks; Atmospheric modeling; Biological system modeling; Equations; Forecasting; Mathematical model; Predictive models; BP neural network; GM(1, N); annual potential evaporation; self-memory;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5583116
