Prediction Model of Tongguan Elevation Changes in Flood Seasons

Abstract

Accurate prediction of Tong guan Elevation has important realistic significance in flood control of lower Weihe River. The existing predictive models of Tong guan Elevation Changes cannot use the historical data to forecast the possible changes of the nest year. This paper proposes a modeling method, using fast neural networks and feature selection techniques, completing the prediction of Tong guan Elevation Changes in Flood Seasons in the next year by using the past historical data to build the training model. This paper verifies the validity of the model through the collected data during the flood seasons, it confirms the validity of the proposed modeling approach.