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In this thesis, a BP neural network based GA (Genetic Algorithm) is proposed to take advantage of their complementary ability of local and global search for optimum solutions. To show the effectiveness of this novel HGA (Hybrid GA), We have respectively developed two application-oriented algorithm for the design of simulation experiments that are widely used in a variety of data processing problems. Several simulation experiments on the data procesing are designed based on the proposed HGA, also experimental simulations are performed to justify the effectiveness of the HGA. Simulation results demonstrate that as compared with corresponding results yielded from other exiting design algorithms, the strategy design by our HGA approach are with better performance and less computation time.

Research on the Hybrid Algorithm on the Basis of BP Neural Network and the Improved Genetic Algorithm