Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007) Research on Threshold Denoising of FPRGA Haier International Training Center, Qingdao, China July 30-August 01 ISBN: 0-7695-2909-7
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SNPD.2007.41
Genetic algorithm (GA) was widely used to engineering and optimization fields. The performance of GA and extension of its application fields were affected by the limitation of its code. Floating point representation (FPR) is super to other codes in function and constraint optimization fields. Noise was brought by the FPR in selection and crossover operation, its influence to the performance of GA was not noticed by researchers. In this paper, the property of the noise in FPR is mostly analyzed in inherit operation. The mechanism of denoising in FPR is researched with wavelet threshold coefficient. Denoising is implemented by mutation. That wavelet theory used in floating point representation genetic algorithm (FPRGA) is credible for reducing noise level, the method is feasible, is indicated by its results of research and experiment.
Index Terms:
Genetic Algorithm; Wavelet Coefficient; Threshold; Denoising Mutation
Citation:
MingYi Cui, XinXiang Zhang, HuiChao Mi, "Research on Threshold Denoising of FPRGA," snpd, vol. 1, pp.3-8, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007), 2007 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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