Researches On Some Key Issues Of Hydrology And Water Resources Based On Intelligent Algorithm

Water is the source of life and the most active factor and most extensive affect in the eco-environmental system. Meanwhile, it is an important resource and can not be replaced in industrial and agricultural production process. Today, the water system has evolved into a multi-objective, multi-attribute, multi-level, multi-functional and multi-stage complex giant system. With the breadth and depth of the system expansion, it is difficult for the traditional methods of water resource systems to deal with modern high-dimensional, non-convex and nonlinear complex issues. Recent years, with rapid development of the modern applied mathematics and computer technology, artificial intelligence computation theory and analysis methods have been proposed to solve complex system problems. The introduction of these methods has greatly facilitated the development of systems analysis techniques and water scientific information analysis and calculation. So there is a very wide space for further research in this area.Based on learning of a variety of new theories and analysis techniques, some new ideas and new methods are used, and some progress has been made in analysis of hydrology and water resources. In this paper, the research works and innovations are as follows:(1) The characteristics analyses of time and frequency domain of the Morlet wavelet transform are studied; The effect of the change of wavelet dilation and translation factor on the time and frequency domain resolution is analyzed; The principle and formula of the Morlet wavelet period recognition are derived.(2)A quick, simple and practical algorithm of coefficients of non-orthogonal wavelet transform is derived form the Parseval theorem and convolution theorem.The method turns non-orthogonal wavelet transform coefficient calculation to the frequency domain calculation, takes advantage of the FFT algorithm, has the advantages of high operation speed and high programming efficiency and provides a algorithm basis for identification the period by the Morlet wavelet.(3)The method integrating simulated annealing algorithm and progressive optimization algorithm is proposed for the optimal operation model for hydropower system. The effectiveness is proved to be suitable for solving optimization problem with complex constraints by this algorithm; The common "local optimization" problem in intelligent algorithm is solved; The theory of optimization scheduling decisions of hydropower systems is developed.(4)The prediction model of neural network is established based on wavelet theory which combines advantages of wavelet theory and neural network. The runoff of river is predicted with the nonlinear simulation capabilities of wavelet neural networks, achieving good results of the simulation and prediction. The multi-faceted comparison and analysis of runoff prediction results and impact of spatial and temporal factors are carried out.(5)In order to solve the problem of linearization, complexity and poor accuracy for parameter estimate of Muskingum Routing Model, this paper introduces three modern intelligent algorithms - Genetic Algorithm (GA), Simulated Annealing Algorithm (SA) and Particle Swarm Optimization Algorithm (PSO) for the parameter calibration of Muskingum model. Through specific simulation, the results of five methods are produced. Then according to the calculation, comparison and analysis of five methods comprehensively, it is found that the results of three modern intelligent algorithms are fit significantly and better than traditional methods.