  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.
