A Study On Genetic Algorithm And Its Application To Water Problem

Genetic algorithm (GA) is one of the key technologies for artificial intelligence and is deemed as an important subject of investigations in various countries. Main works in the paper are illustrated as follows.1. This paper presents a systemic review about the state-of -art progresses of genetic algorithm(GA) both at home and abroad, gives an analysis of the concepts adopted and the characteristics of technological processing for some models, summarizes the application of GA on water, and points out the tendencies that deserve attention.2. Based on the study of the reason of premature convergence in canonical genetic algorithms, a new genetic algorithm is proposed in this paper. The experiment results and theory analysis show that such an improved genetic algorithm can find global optimal beyond premature convergence efficiently.3. Proposed in this paper is a novel genetic algorithm (MAGA) , which not only can keep the population diversity but also has quicker convergence speed. It is applied to optimizing functions with multi-model. Computer simulation results prove its validity.4. A series of applications of NGA and MAGA are made, which include optimizing the parameters of Muskingum routing model with SGA and NGA, optimizing the parameters of the Formula of Storm Intensity with SGA and MAGA. The results indicate that these algorithms are practical and efficient on water.II5. Research involving some sort of combination of genetic algorithms (GAs) and Artificial Neural Networks (ANNs) has attracted a lot of attention recently. Firstly, this article presents a brief review of the state of the art and research prospects in this area. Secondly, the MAGA algorithm coding in binary is engaged to optimize the weights and topology of multi-layer neural network. Furthermore, the experiment result, which establishing the model of evaluation of flood disaster effect, shows that by combining the binary-coded GA with BP algorithm, the entrapment in local optical optimum of BP and the premature of GA can be prevented efficiently and satisfactorily results are obtained.