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Time Related Association rule mining is a kind of sequence pattern mining for sequential databases. In this paper, a method of Generalized Association Rule Mining using Genetic Network Programming (GNP) with MBFP(Multi-Branch and Full-Pathes) processing mechanism has been introduced in order to find time related sequential rules more efficiently. GNP represents solutions as directed graph structures,...
Genetic Network Programming (GNP) is an evolutionary algorithm derived form GA and GP. It can deal with complex problems in dynamic environments efficiently and effectively because of its directed graph structure, reusability of nodes, and implicit memory function. This paper proposed a new method to optimize GNP algorithm by strengthening its exploitation ability through extracting and using rules...
Genetic Network Programming (GNP) extended from GA and GP is competent for the complex problems in dynamic environments because of its directed graph structure, reusability of nodes and implicit memory function. In this paper, a new method to extract and accumulate rules from GNP is proposed. The general idea is to update the fitness values of the rules accumulatively, rather than just replacing them...
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