2008/05/29 by H. O. Ghaffari, H. Owladeghaffari, Mostafa Sharifzadeh +2 · 9 citations
Computer Science · Engineering · Mathematics · #Algorithm #Artificial intelligence #Computer science #Data mining #Engineering #Flowchart #Fuzzy logic #Fuzzy set #Geoscience and Mining Technology #Geotechnical engineering #Granular computing #Granulation #Hydraulic Fracturing and Reservoir Analysis #Mathematics #Rough Sets and Fuzzy Logic #Rough set #Soft computing #cs.AI
paper · pdf · doi:10.1016/j.ijrmms.2008.09.001
published in International Journal of Rock Mechanics and Mining Sciences 46(3), 577-589 (Elsevier BV)
arxiv created 2008/05/29 · openalex publication_date 2008/10/31 · arxiv updated 2014/07/29 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
This paper describes application of information granulation theory, on the design of rock engineering flowcharts. Firstly, an overall flowchart, based on information granulation theory has been highlighted. Information granulation theory, in crisp (non-fuzzy) or fuzzy format, can take into account engineering experiences (especially in fuzzy shape-incomplete information or superfluous), or engineering judgments, in each step of designing procedure, while the suitable instruments modeling are employed. In this manner and to extension of soft modeling instruments, using three combinations of Self Organizing Map (SOM), Neuro-Fuzzy Inference System (NFIS), and Rough Set Theory (RST) crisp and fuzzy granules, from monitored data sets are obtained. The main underlined core of our algorithms are balancing of crisp(rough or non-fuzzy) granules and sub fuzzy granules, within non fuzzy information (initial granulation) upon the open-close iterations. Using different criteria on balancing best granules (information pockets), are obtained. Validations of our proposed methods, on the data set of in-situ permeability in rock masses in Shivashan dam, Iran have been highlighted.