Modification of rock mass rating system using soft computing techniques

  • Hima Nikafshan RadEmail author
  • Zakaria Jalali
Original Article


Classification systems such as rock mass rating (RMR) are used to evaluate rock mass quality. This paper intended to evaluate RMR based on a fuzzy clustering algorithm to improve linguistic and empirical criteria for the RMR classification system. In the proposed algorithm, membership functions were first extracted for each RMR parameter based on the questionnaires filled out by experts. RMR clustering algorithm was determined by considering the percent importance of each parameter in the RMR classification system. In all implementation stages of the proposed algorithm, no empirical judgment was made in determining the classification classes in the RMR system. According to the obtained results, the proposed algorithm is a powerful tool to modify the rock mass rating system and can be generalized for future research.


RMR system based on continuous rating Multi-objective optimization Genetic algorithm Fuzzy clustering algorithm 



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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Computer ScienceTabari University of BabolBabolIran
  2. 2.Department of Mining Engineering, Higher Educational Complex of ZarandShahid Bahonar University of KermanKermanIran

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