Machine Learning Emulation in Nature-inspired Computation Systems

Jianhao Tan, Jing Zhang, Fu Guo

Abstract


The whole frame of nature_inspired computation systems is inquired into, the characteristics of machine learning in nature_inspired computation systems are researched, and a particular scheme on machine learning in nature_inspired computation systems is designed with environment being gathered present data; study unit adopting fuzzy optimizatio algorithm based on genetic algorithm; knowledge base adopting fuzzy optimization BP neural networks; executive unit being complicated industry process. The fuzzy optimizatio learning algorithm of fuzzy optimization BP neural networks is built, the flow chart of the algorithm is constructed, and the emulation test is made. At last, the design criteria of flash metal comsuption are obtained, and the stability of the algorithm is verified through this example. The result shows that machine learning makes nature_inspired computation systems be able to gain know; edge automatically, their quality improved, their intelligent level advanced, and machine learning will greatly influence the memory mode, information input mode and system structures of nature_inspired computation systems.


Full Text: PDF DOI: 10.5539/cis.v2n3p15

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This work is licensed under a Creative Commons Attribution 3.0 License.

Computer and Information Science   ISSN 1913-8989 (Print)   ISSN 1913-8997 (Online)
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