Application of GA-RBF Neural Network Model in River Temperature Prediction

River temperature prediction is an important project in the environmental impact assessments. To overcome the limitation of the traditional river temperature prediction method, Radial Basis Function neural network (RBF) based on genetic algorithm (GA) was proposed to predict river temperature. Genetic algorithm was applied to optimize the parameters of the neural network, and overcome the over-fitting problem and the local minima problem. MATLAB was applied to simulate the model. Theoretical analysis and simulations show that the prediction precision was improved greatly and the model had better generalization performance.