Artificial neural network model for flood water level forecasting
ZHU Xing-ming~1, LU Chang-na~2, WANG Ru-yun~2,BAI Jing-Yi~1(1. China Institute of Water Resources and Hydropower Research, Beijing 100044, China; 2. Hohai University, Nanjing 210098, China)
The artificial neural network technology is applied to establish the model for forecasting the flood water level based on the data of upstream hydrological station and local station. The deterministic coefficient in forecasting norm for hydrology is taken as the objective function. For improving the network training speed and forecasting the probable high water level exceeding the highest water level in history, a standardized method is given to treat the data of input layer and output layer. The proposed forecasting model is applied to analyze the hydrological data of two stations located in Beijiang River, Zhujiang Delta. The result shows that by reasonable selection of original data for input layer element and forecasting period, satisfactory forecast precision can be obtained.