A novel method for locating the critical slip surface of a soil slope. (September 2020)

• Record Type: Journal Article
• Authors: Li, S.H.; Wu, L.Z.; Luo, X.H.
• Is Part Of: Engineering applications of artificial intelligence. Volume 94(2020)
• Publication Date: 2020-09
• Subjects: Slope stability -- Critical slip surface -- Minimum safety factor -- Improved whale optimization algorithm; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2020.103733
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: Calculating the minimum slope safety factor or locating the critical slip surface of a soil slope is a complex optimization problem. This paper describes an improved whale optimization algorithm (IWOA) for locating the critical slip surface of a soil slope. Locating a critical slip surface is transformed into a three-dimensional problem from a high-dimensional optimization. Combined with the Morgenstern–Price method, IWOA is compared against other optimization techniques in an experimental study. Test results using 13 benchmark functions show that IWOA significantly outperforms the conventional whale optimization algorithm (WOA) and particle swarm optimization (PSO). The IWOA method is then used to search for the critical slip surfaces of four slopes. The results show that IWOA again performs better than WOA and PSO in locating the critical slip surface.