Graphical Estimation of Permeability Using RST&NFIS

dc.creatorOwladeghaffari, H.
dc.creatorPedrycz, K. Shahriar W.
dc.date2008-04-02
dc.date.accessioned2026-07-07T09:29:52Z
dc.date.available2026-07-07T09:29:52Z
dc.descriptionThis paper pursues some applications of Rough Set Theory (RST) and neural-fuzzy model to analysis of "lugeon data". In the manner, using Self Organizing Map (SOM) as a pre-processing the data are scaled and then the dominant rules by RST, are elicited. Based on these rules variations of permeability in the different levels of Shivashan dam, Iran has been highlighted. Then, via using a combining of SOM and an adaptive Neuro-Fuzzy Inference System (NFIS) another analysis on the data was carried out. Finally, a brief comparison between the obtained results of RST and SOM-NFIS (briefly SONFIS) has been rendered.
dc.description6 pages;NAFIPS08
dc.identifierhttps://arxiv.org/abs/0804.0353
dc.identifierhttp://arxiv.org/abs/0804.0353
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/157947
dc.subjectNeural and Evolutionary Computing
dc.subjectArtificial Intelligence
dc.subjectF.4.1
dc.titleGraphical Estimation of Permeability Using RST&NFIS
dc.typetext

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