New Method And Its Application To Water Science Information Analysis And Calculation

Water Science information analysis and calculation is continuously among development, and it is a hotspot, especially in recent 10-20 years. Along with the science and technology progress, many excellent research results come forth, making this territory a vast space worthy of study.Under the auspices of the National Key Project for Basic Research of China (No.2002CB412301) and National Natural Science Foundation of China(No.40271024), this thesis applies modern new theories and technique(such as Support Vector Machine, Particle Swarm Optimization, Artificial Neural Network, Wavelet Analysis, etc.) to systematically study the new methods in Water Science information analysis and calculation, and proposes various new hybrid models of prediction, which can be widely applied to the Water Science and other associated areas. Principal findings are concluded as follows.(1) Support Vector Machine(SVM) as a machine learning method is based on the solid theory foundation of Statistical Learning Theory, and focuses on the small samples. The theory of SVM and its characteristics were expatiated, and then proposed the application of SVM to the slope stability forecasting, sediment-carrying capacity forecasting and prediction of annual electricity consumption.