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arXiv 0804.0352cs.NEcs.AI
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Permeability Analysis based on information granulation theory

Amirkabir University of Technology(阿米尔卡比尔理工大学)

M. Sharifzadeh, H. Owladeghaffari, K. Shahriar, E. Bakhtavar

英文摘要:

This paper describes application of information granulation theory, on the analysis of "lugeon data". In this manner, using a combining of Self Organizing Map (SOM) and Neuro-Fuzzy Inference System (NFIS), crisp and fuzzy granules are obtained. Balancing of crisp granules and sub- fuzzy granules, within non fuzzy information (initial granulation), is rendered in open-close iteration. Using two criteria, "simplicity of rules "and "suitable adaptive threshold error level", stability of algorithm is guaranteed. In other part of paper, rough set theory (RST), to approximate analysis, has been employed >.Validation of the proposed methods, on the large data set of in-situ permeability in rock masses, in the Shivashan dam, Iran, has been highlighted. By the implementation of the proposed algorithm on the lugeon data set, was proved the suggested method, relating the approximate analysis on the permeability, could be applied.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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