Douhe Reservoir Flood Forecasting Model Based on Data Mining Technology

Calculating flood based on rainfall is an important part of hydrological forecast. However, due to the diversity and complexity of factors affecting the relationship between rainfall and runoffs, using the perspective of mechanism to simulate the forming of flood through rainfall is often difficult. In this paper, flood forecast model is constructed based on Artificial Neural Networks (ANN) and Genetic Programming (GP), using actual data to mine the relationship among rainfall, pre rain and net rain, to avoid the flaws of constructing actual mathematical expression in advance, and automatically search for optimal structure. Practice has approved that applying data mining technique on flood forecasting of Douhe Reservoir is able to achieve outstanding results.