Title :
River Ice Forecasting Based on Genetic Neural Network
Author :
Wang, Zhixing ; Li, Chengzhen
Author_Institution :
Water Conservancy & Hydropower Inst., Xi´´an Univ. of Technol., Harbin, China
Abstract :
Based on the analysis of the factors caused ice flood, the paper selected appropriate forecasting factors, established neural network model of ice forecasting combining genetic algorithm (GA) with Levenberg-Marquardt BP(LMBP) neural network. The GA-LMBP algorithm is to train globally using genetic learning algorithm firstly, then train accurately using LMBP algorithm, overcoming the defects of traditional BP algorithm such as slow convergent rate and local minimum. It has achieved good results through applying the model to forecast break-up date in Yilan and Jiamusi sections of Songhua River.
Keywords :
backpropagation; floods; forecasting theory; genetic algorithms; geophysics computing; hydrological techniques; ice; neural nets; rivers; Levenberg-Marquardt BP neural network; Songhua River; genetic algorithm; genetic learning algorithm; genetic neural network; ice flood; river ice forecasting; Algorithm design and analysis; Genetic algorithms; Hydroelectric power generation; Ice; Mathematical model; Neural networks; Predictive models; Rivers; Technology forecasting; Water conservation;
Conference_Titel :
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4994-1
DOI :
10.1109/ICIECS.2009.5364590