气候变化领域集成服务门户(CCPortal): Stability prediction of Himalayan residual soil slope using artificial neural network

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DOI	10.1007/s11069-020-04141-2
	Stability prediction of Himalayan residual soil slope using artificial neural network
	Ray A.; Kumar V.; Kumar A.; Rai R.; Khandelwal M.; Singh T.N.
发表日期	2020
ISSN	0921030X
起始页码	3523
结束页码	3540
卷号	103 期号:3
英文摘要	In the past decade, advances in machine learning (ML) techniques have resulted in developing sophisticated models that are capable of modelling extremely complex multi-factorial problems like slope stability analysis. The literature review indicates that considerable works have been done in slope stability using ML, but none of them covers the analysis of residual soil slope. The present study aims to develop an artificial neural network (ANN) model that can be employed for evaluating the factor of safety of Shiwalik Slopes in the Himalayan Region. Data obtained from numerical analysis of a residual soil slope were used to develop two ANN models (ANN1 and ANN2 utilising eleven input parameters, and scaled-down number of parameters based on correlation coefficient, respectively). A four-layer, feed-forward back-propagation neural network having the optimum number of hidden neurons is developed based on trial-and-error method. The results derived from ANN models were compared with those achieved from numerical analysis. Additionally, several performance indices such as coefficient of determination (R2), root mean square error, variance account for, and residual error were employed to evaluate the predictive performance of the developed ANN models. Both the ANN models have shown good prediction performance; however, the overall performance of the ANN2 model is better than the ANN1 model. It is concluded that the ANN models are reliable, valid, and straightforward computational tools that can be employed for slope stability analysis during the preliminary stage of designing infrastructure projects in residual soil slope. © 2020, Springer Nature B.V.
关键词	Artificial neural network Machine learning Residual soil Slope stability
英文关键词	artificial neural network; machine learning; prediction; residual soil; slope dynamics; slope stability; stability analysis; Himalayas; Siwalik Hills
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/205895
作者单位	Department of Mining Engineering, Indian Institute of Technology (BHU) Varanasi, Varanasi, India; School of Engineering, Information Technology and Physical Sciences, Federation University Australia, Ballarat, Australia; Department of Earth Sciences, Indian Institute of Technology Bombay, Mumbai, India
推荐引用方式 GB/T 7714	Ray A.,Kumar V.,Kumar A.,et al. Stability prediction of Himalayan residual soil slope using artificial neural network[J],2020,103(3).
APA	Ray A.,Kumar V.,Kumar A.,Rai R.,Khandelwal M.,&Singh T.N..(2020).Stability prediction of Himalayan residual soil slope using artificial neural network.Natural Hazards,103(3).
MLA	Ray A.,et al."Stability prediction of Himalayan residual soil slope using artificial neural network".Natural Hazards 103.3(2020).