ORIGINAL RESEARCH article

Front. Earth Sci.

Sec. Geohazards and Georisks

Volume 13 - 2025 | doi: 10.3389/feart.2025.1612042

This article is part of the Research TopicNatural Disaster Prediction Based on Experimental and Numerical MethodsView all 17 articles

The Assessment of Slope Stability Based on the Improved Entropy Weight-Grey Target Theory

Provisionally accepted
Bing  ZhaoBing Zhao1Ning  LiNing Li2Cao  YuanCao Yuan3Xin-Bao  GuXin-Bao Gu1*
  • 1Nanyang Institute of Technology, Nanyang, China
  • 2Nanyang Natural Resources Research and Planning Institute, Nanyang, China
  • 3Beijing Forestry University, Beijing, Beijing, China

The final, formatted version of the article will be published soon.

Landslide is one of serious natural hazard globally. While the traditional grey target model has long served as an effective tool for slope stability assessment, its predictive accuracy remains questionable due to the inherent correlations among evaluation indicators. To mitigate this limitation, this study introduces an enhanced entropy weight-grey target theory for slope stability evaluation. The proposed model innovates in two key aspects: first, it substitutes the covariance matrix in the Mahalanobis distance calculation with a correlation coefficient matrix, thereby addressing indicator interdependencies; second, it adapts the positive and negative ideal solutions from the TOPSIS model to define the corresponding target centers in the grey target framework. The improved model's efficacy is validated through an engineering case study. The findings confirm that the proposed method not only offers a feasible approach for slope stability assessment but also demonstrates superior predictive accuracy compared to the traditional grey target model. This research contributes a novel methodology and conceptual framework for future slope stability evaluations..

Keywords: assessment, slope stability, Improved, entropy weight-grey target theory, Risk level

Received: 15 Apr 2025; Accepted: 04 Jun 2025.

Copyright: © 2025 Zhao, Li, Yuan and Gu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Xin-Bao Gu, Nanyang Institute of Technology, Nanyang, China

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