A sudden downward movement of the geomaterial, either composed of soil, rock, or a mixture of both, along the mountain slopes due to various natural or anthropogenic factors is known as a landslide. The Himalayan Mountain slopes are either made up of residual soil or rocks. Residual soil is formed from weathering of the bedrock and mainly occurs in gentle-to-moderate slope inclinations. In contrast, steep slopes are mostly devoid of soil cover and are primarily rocky. A stability prediction system that can analyse the slope under both the condition of the soil or rock surface is missing. In this study, artificial neural network technology has been utilised to predict the stability of jointed rock and residual soil slope of the Himalayan region. The database for the artificial neural network was obtained from numerical simulation of several residual soils and rock slope models. Nonlinear equations have been formulated by coding the artificial neural network algorithm. An android application has also been developed to predict the stability of residual soil and rock slope instantly. It was observed that the developed android app provides promising results in predicting the factor of safety and stability state of the slopes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.