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Design and Implementation of GA-ANN-GA System Based on Heuristic Genetic Algorithms

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Tutor: ChenZeLin
School: South China University of Technology
Course: Applied Computer Technology
Keywords: Genetic Algorithm,Artificial Neural Network,GA-ANN-GA Model,MVC
Type: Master's thesis
Year:  2011
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Human increasingly adept at syudying and simulating life phenomenon and law of nature to get knowledge, then evolve and filter them into other fields successfully. Genetic Algorithm is a high efficient, parallel and global searching algorithm, which was learned from natural selection and genetic mechanism, and was produced from various subjects integrating and infiltrating with each other. Genetic algorithm is widely used in solving the intelligent optimization problem calculation method. Due to genetic algorithm can effectively solution of belonging to NPC¡¯s type combinatorial optimization problem and nonlinear model, the multi-objective function optimization problems, thus getting multidisciplinary extensive attention, became one of the best tools. Its research history is short,early it is a constructed artificial system model of simulating the mechanisms of biological evolution from attempting to explain the complexity process of biological in the natural system. Formed in recent years around the world boom of evolutionary computation, computational intelligence became one of the major directions of artificial intelligence research, as well as the subsequent rise of artificial life research, so that genetic algorithms is concerned broad.By analysis and comparison of the Genetic Algorithm (GA) and the traditional algorithms in the area, a new algorithm based on GA is put forward to settle the control of Navigating in Space. And the experimental results show that the scheme is feasible in practice. In our algorithm, we improve the performance of GA by the following scheme: we bring forward a new coding scheme based on which new mutation operators are designed and the cross operator is discarded. A new heuristic Genetic pattern derived from "Required Genetic" is put forward and realized. Further, a kind of system: "GA-ANN-GA" is brought forward and is proved to be advanced and reliable.What¡¯s more, we adopted a lot of advanced ideal of software development, such as Model-View-Controller (MVC), Test Driven Design and so on .So the code will be robust and transplantable. We expect this universal laboratory achievement is easy to transplant and expand. Finally, we sum up the experiences of the work, discuss its deficiencies and propose some possible corresponding solutions.
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