Reliability analysis of reinforced soil slope stability using GA-ANFIS, RFC, and GMDH soft computing techniques

Rahul Ray; Shiva Shankar Choudhary; Lal Bahadur Roy; Mosbeh R. Kaloop; Pijush Samui; Pradeep U. Kurup; Jungkyu Ahn; Jong Wan Hu

Case Studies in Construction Materials (Jul 2023)

Reliability analysis of reinforced soil slope stability using GA-ANFIS, RFC, and GMDH soft computing techniques

Rahul Ray,
Shiva Shankar Choudhary,
Lal Bahadur Roy,
Mosbeh R. Kaloop,
Pijush Samui,
Pradeep U. Kurup,
Jungkyu Ahn,
Jong Wan Hu

Affiliations

Rahul Ray: Department of Civil Engineering, GLA University Mathura, Mathura, Uttar Pradesh, India
Shiva Shankar Choudhary: Department of Civil Engineering, National Institute of Technology Patna, Patna, Bihar, India
Lal Bahadur Roy: Department of Civil Engineering, National Institute of Technology Patna, Patna, Bihar, India
Mosbeh R. Kaloop: Department of Civil and Environmental Engineering, Incheon National University, the Republic of Korea; Incheon Disaster Prevention Research Center, Incheon National University, the Republic of Korea; Public Works and Civil Engineering Department, Mansoura University, Egypt
Pijush Samui: Department of Civil Engineering, National Institute of Technology Patna, Patna, Bihar, India
Pradeep U. Kurup: Department of Civil and Environmental Engineering, University of Massachusetts Lowell, Lowell, USA
Jungkyu Ahn: Department of Civil and Environmental Engineering, Incheon National University, the Republic of Korea; Incheon Disaster Prevention Research Center, Incheon National University, the Republic of Korea
Jong Wan Hu: Department of Civil and Environmental Engineering, Incheon National University, the Republic of Korea; Incheon Disaster Prevention Research Center, Incheon National University, the Republic of Korea; Corresponding author at: Department of Civil and Environmental Engineering, Incheon National University, the Republic of Korea.

Journal volume & issue: Vol. 18
p. e01898

Abstract

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Soil is a heterogeneous medium, the characteristics that determine soil slope stability are highly variable, making the analysis a difficult task. The present research approach is switching from deterministic to probabilistic in order to account for the variability in soil properties. This research presents the use of three soft-computing techniques to evaluate reinforced soil slope reliability based on slope stability: Genetic Algorithm based Adaptive Network based Fuzzy Inference System (GA-ANFIS), Random Forests Classifier (RFC), and Group Method of Data Handling (GMDH). Shear strength parameters c (cohesion), ϕ (angle of shearing resistance) and ϒ (unit weight) are used as input variables, while Factor of Safety of Reinforced Soil Slope (F) is used as an output variable to determine the stability of a soil slope of a certain height. The Models were also evaluated using various assessment parameters and GA-ANFIS outperformed having some testing outputs as NS= 0.997, RMSE= 0.017, VAF= 99.731 %, Bias Factor= 1.002, PI= 1.998, R2 = 0.997, GPI= 6.6E-08, U95 = 0.627, tstat= 0.247 and β = 1.543. The GA-ANFIS model outperformed the GMDH and RFC models, according to the findings of the analyses using Taylor diagram and ROC curve. As a result, the GA-ANFIS model can be utilized as a reliable soft computing technique to analyze reinforced soil slope stability.

Published in Case Studies in Construction Materials

ISSN: 2214-5095 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering: Materials of engineering and construction. Mechanics of materials
Website: https://www.journals.elsevier.com/case-studies-in-construction-materials

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