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Modification of rock mass rating system using soft computing techniques

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Abstract

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.

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Authors and Affiliations

  1. College of Computer Science, Tabari University of Babol, Babol, Iran

    Hima Nikafshan Rad

  2. Department of Mining Engineering, Higher Educational Complex of Zarand, Shahid Bahonar University of Kerman, Kerman, Iran

    Zakaria Jalali

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  1. Hima Nikafshan Rad
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  2. Zakaria Jalali
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Correspondence to Hima Nikafshan Rad.

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Nikafshan Rad, H., Jalali, Z. Modification of rock mass rating system using soft computing techniques. Engineering with Computers 35, 1333–1357 (2019). https://doi.org/10.1007/s00366-018-0667-6

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