Back analysis based on SOM-RST system

TL;DR

This paper presents a novel method combining SOM and RST for back analysis of mine wall failure, integrating hard and soft computing techniques to handle incomplete information effectively.

Contribution

It introduces a new approach that combines Self Organizing Map and rough set theory with finite difference method for practical back analysis of mine structures.

Findings

Successfully applied to Jeffrey mine wall failure case

Effectively handles missing information in analysis

Integrates hard and soft computing for improved accuracy

Abstract

This paper describes application of information granulation theory, on the back analysis of Jeffrey mine southeast wall Quebec. In this manner, using a combining of Self Organizing Map (SOM) and rough set theory (RST), crisp and rough granules are obtained. Balancing of crisp granules and sub rough granules is rendered in close-open iteration. Combining of hard and soft computing, namely finite difference method (FDM) and computational intelligence and taking in to account missing information are two main benefits of the proposed method. As a practical example, reverse analysis on the failure of the southeast wall Jeffrey mine is accomplished.