The application of parallel extreme learning machine in flood forecasting
Liu Jin · Journal of Northwest University · 2015
To study the neural network model to forecast floods,requires the model to ensure a certain operating efficiency and accuracy. In this paper,parallel extreme learning machine is used to establish flood forecasting models. A flood forecasting model is established,which is in the application level,and can be used to forecast flood of Weihe River and Hanjiang River. Parallel extreme learning machine has the advantages both of extreme learning machine and parallel computing,no iterative adjustment of hidden nodes is necessary,it can predict by post-training; it is of high efficiency,better forecasting,and has a certain practical value.