← Volver a resultados
Ficha bibliográfica · Consulta y acceso
Artículo

Stability Evaluation of Granite Residual Soil Slopes Using an Improved G1-EWM Combined Weighting Cloud Model

Longfei Jiang et al · Wiley · 2026

Acceso abierto disponible
Lectura rápida. Revisá los datos básicos del recurso y luego accedé al contenido desde el botón principal. En esta ficha solo se muestra la información necesaria para identificar la obra, citarla y abrirla.

Acceso al recurso

Entrá al contenido desde la opción principal o elegí otra fuente disponible.

Acceso principal

Acceso abierto disponible

Recurso identificado como acceso abierto, sin confirmar automáticamente si es texto completo directo.
Abrir recurso

Resumen

Descripción general del contenido del recurso.

Granite residual soil (GRS) slopes are widely distributed in the humid and rainy regions around the world. Due to their unique mineral and pore composition, these soils exhibit a loose structure and are prone to softening and disintegration upon wetting. Such slopes often suffer from collapses and landslides along highway in the southeast coast of China, posing a serious threat to transportation safety. Therefore, it is necessary to evaluate the stability of GRS slopes. This study investigates slopes along three expressways in Guangdong Province, China. A systematic analysis of instability mechanisms was first conducted. Based on this analysis, an evaluation system was developed. It includes four primary indicators: geomorphology and geology, geotechnical character, environmental factors, and engineering activities. These are further divided into 13 secondary indicators. Subsequently, the study proposes an improved combined weighting approach to address uncertainties. Subjective fuzziness is quantified by enhancing the order relation method (G1 method) with Monte Carlo simulation. Meanwhile, objective weight distortion is mitigated by optimizing the entropy weight method (EWM) with a sigmoid function, and the linear weighting method is adopted to achieve a scientific balance between subjective and objective weights. Subsequently, a slope stability evaluation model is constructed based on the cloud model theory. A case study of K21 slope of the Yunmao Expressway is conducted. The evaluation result from the model is consistent with the field situation. Twenty typical slopes from the three expressways were furtherly selected for model verification. Results indicate that the proposed model increases accuracy rates by 10% and 5% higher than the analytic hierarchy process (AHP) and the EWM, respectively. The method proposed in this paper can effectively and accurately evaluate the stability of GRS slopes. The method uniquely combines subjective and objective factors and integrates qualitative and quantitative analyses for stability evaluation.

Cómo citar

Elegí el formato que necesitás y copiá la referencia al portapapeles.

APA 7

al, L. J. E. (2026). Stability Evaluation of Granite Residual Soil Slopes Using an Improved G1-EWM Combined Weighting Cloud Model. https://doi.org/10.1155/adce/5335973

MLA

al, Longfei Jiang et. "Stability Evaluation of Granite Residual Soil Slopes Using an Improved G1-EWM Combined Weighting Cloud Model." 2026. https://doi.org/10.1155/adce/5335973.

Chicago

al, Longfei Jiang et. 2026. "Stability Evaluation of Granite Residual Soil Slopes Using an Improved G1-EWM Combined Weighting Cloud Model.". https://doi.org/10.1155/adce/5335973.

Harvard

al, L. J. E. 2026, Stability Evaluation of Granite Residual Soil Slopes Using an Improved G1-EWM Combined Weighting Cloud Model, Wiley, available at: https://doi.org/10.1155/adce/5335973 [Accessed 30 Jun. 2026].

Compartir e imprimir

Guardá la ficha, copiá su enlace permanente o imprimila como PDF.

Exportar referencia

Si usás un gestor bibliográfico, podés exportar el registro en los formatos más comunes.

Detalles del recurso

Información bibliográfica útil para confirmar que se trata del material correcto.

Título
Stability Evaluation of Granite Residual Soil Slopes Using an Improved G1-EWM Combined Weighting Cloud Model
Autor / colaboradores
Longfei Jiang et al
Editorial
Wiley
Año de publicación
2026
ISSN
1687-8094
ISSN
1687-8094
Idioma
eng
Copiado