Risk Assessment of the Rockburst Intensity in a Hydraulic Tunnel Using an Intuitionistic Fuzzy Sets-TOPSIS Model

Abstract

Rockbursts pose a significant threat to the safety of construction workers during construction periods. Many factors control its occurrence. To evaluate the intensity level of rockburst in hydraulic tunnels accurately, the intuitionistic fuzzy sets-TOPSIS model is first introduced. And, the decisive matrix is constructed. Then, the weighed decisive matrix is calculated. Finally, the degree of membership at different levels regarding the rockburst intensity is obtained. According to the ranking sequence of the membership degree, the risk level that corresponds to the maximum membership degree is the final assessment level. The conclusions are drawn that assessing the level of rockburst intensity using the proposed method is feasible. Compared with the traditional method, the proposed model has sufficient usage of original data, minor information loss, and broader application. And, their judgments under inherent uncertainty in the proposed model can be conveyed. More significantly, the degree of indeterminacy can be handled adequately in the evaluation. The proposed method not only can deal with vague information but also ease our workload. The efficiency and accuracy can be improved. In total, it can provide a new route for the intensity prediction of rockburst in the future.

Level evaluation of concrete dam fractures based on game theory combination weighting-normal cloud model

“…Many researchers have adopted methods to accurately assess the hazard grade of concrete dam fractures (Zhou et al, 2016;GuWu and Ma, 2022). For example, Zhang et al considered the influence of cracks on the structure and durability of dams (ZHANG et al, 2022).…”

Prediction of Rock Burst Intensity Based on Multi-Source Evidence Weight and Error-Eliminating Theory

“…A number of indexes should be synthesized for the rock burst prediction and discrimination before the accident, while the information of these indexes has strong uncertainty and fuzziness. To effectively predict and discriminate rock burst, mathematical algorithms are used to process fuzzy information in rock burst studies in recent years.Li proposed an intelligent rockburst prediction model with sample category balance using feedforward neural network and Bayesian optimization; Gu (Gu et al, 2022) established a rock burst prediction model based on Intuitionistic Fuzzy Sets-TOPSIS; Kidega (Kidega et al, 2022) build an uncertainty model of rock burst prediction based on gradient boosting algorithms; Zhang (Zhang, 2022) used hybrid PSO-BP neural network to forecast rock burst. Xu (Xu et al, 2022) constructed a model based on FA-SSA-PNN calculate rock burst.…”

The Quality Assessment of Pavement Performance Using the Entropy Weight-Variable Fuzzy Sets Model

“…For example, the system analysis evaluation method [3], the comprehensive evaluation method [4], the extension cloud evaluation method [5], the extension evaluation method [6], the fuzzy compound matter element method [7], the gray fuzzy clustering method [8], the regression analysis method [9], the multivariate statistical techniques [10], the wavelet technique [11], and evaluation method using analytical connection coe cients [12]. ese methods have furthered the development of assessment systems but still exhibited some shortcomings [13]. For example, the comprehensive evaluation index is obtained from the weights of the pavement performance index and thus requires repartitioning the class standard of the synthetic assessment index [14].…”