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Granularity of Knowledge Computed by Genetic Algorithms Based on Rough Sets Theory
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作者 Wenyuan Yang Xiaoping Ye +1 位作者 Yong Tang Pingping Wei 《南昌工程学院学报》 CAS 2006年第2期97-101,121,共6页
Rough set philosophy hinges on the granularity of data, which is used to build all its basic concepts, like approximations, dependencies, reduction etc. Genetic Algorithms provides a general frame to optimize problem ... Rough set philosophy hinges on the granularity of data, which is used to build all its basic concepts, like approximations, dependencies, reduction etc. Genetic Algorithms provides a general frame to optimize problem solution of complex system without depending on the domain of problem.It is robust to many kinds of problems.The paper combines Genetic Algorithms and rough sets theory to compute granular of knowledge through an example of information table. The combination enable us to compute granular of knowledge effectively.It is also useful for computer auto-computing and information processing. 展开更多
关键词 granularity of knowledge Genetic Algorithms Pawlak model Rough set theory information table
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