Rock Mass Quality Evaluation Based on Unascertained Measure and Intuitionistic Fuzzy Sets. (27th April 2020)

• Record Type: Journal Article
• Authors: Wu, Shuliang; Du, Xidong; Yang, Shan
• Other Names: Garg Harish Academic Editor.
• Is Part Of: Complexity. Volume 2020(2020)
• Publication Date: 2020-04-27
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2020/5614581
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : Evaluation of rock mass quality is of great significance to the design and construction of geotechnical engineering. In order to evaluate the quality of engineering rock mass scientifically and deal with the fuzzy information in the rock mass quality evaluation reasonably, a model for evaluation of rock mass quality based on unascertained measure and intuitionistic fuzzy sets (UM-IFS) was proposed. First, the membership of rock mass quality evaluation index was determined by the single index measure function of unascertained measure (UM) theory. Based on the intuitionistic fuzzy sets (IFS) theory, the single index measure evaluation matrix based on IFS (IFS-single index measure evaluation matrix) was obtained. By synthesizing various subjective and objective weighting methods, the range of index weight was determined, and the index weight vector based on IFS (IFS-index weight vector) was constructed. Then, the IFS-single index measure evaluation matrix and the IFS-index weight vector were used to calculate the scores of rock mass samples and evaluate rock mass quality. Finally, fuzzy analysis was performed on the weight of rock mass quality evaluation index. The established model for evaluation of rock mass quality was applied to the underground engineering rock mass in Guangzhou pumped storage power plant, and the evaluation results were compared with the other 4 effective models for rock mass quality evaluation. The results show that rock mass quality evaluation based on UM-IFS is consistent with the actual situation, and the fuzziness of evaluation index weight has no obvious correlation with its value.