This book makes an endeavor to improve the accuracy of hydrological forecasting in three aspects, model inputs, selection of models, and data-preprocessing techniques. Seven input techniques, namely, linear correlation analysis (LCA), false nearest neighbors, correlation integral, stepwise linear regression, average mutual information, partial mutual information, artificial neural network (ANN) based on multi-objective genetic algorithm, are first examined to select optimal model inputs in each prediction scenario. Representative models, such as K-nearest-neighbors (K-NN) model, dynamic...
This book makes an endeavor to improve the accuracy of hydrological forecasting in three aspects, model inputs, selection of models, and data-preproce...
