Rock mechanics modeling based on soft granulation theory

TL;DR

This paper introduces a novel rock engineering modeling approach using information granulation theory combined with soft modeling instruments like SOM, NFIS, and RST, validated on permeability data from a dam site.

Contribution

It presents a new methodology integrating fuzzy and crisp granulation techniques with soft computing tools for improved rock mechanics modeling.

Findings

Effective data granulation balancing methods identified.

Validated approach on real permeability data from Shivashan dam.

Enhanced modeling accuracy with fuzzy and crisp granule integration.

Abstract

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.