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Three Practical Methods for Analyzing Slope Stability
Author(s) -
Shiguang XU,
Shitao ZHANG,
Chuanbing ZHU,
Ying YIN
Publication year - 2008
Publication title -
acta geologica sinica ‐ english edition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.444
H-Index - 61
eISSN - 1755-6724
pISSN - 1000-9515
DOI - 10.1111/j.1755-6724.2008.tb00666.x
Subject(s) - stability (learning theory) , arable land , slope stability , set (abstract data type) , artificial neural network , multivariate statistics , slope stability probability classification , computer science , civil engineering , mathematics , slope stability analysis , geotechnical engineering , geology , engineering , geography , artificial intelligence , machine learning , programming language , archaeology , agriculture
Since the environmental capacity and the arable as well as the inhabitant lands have actually reached a full balance, the slopes are becoming the more and more important options for various engineering constructions. Because of the geological complexity of the slope, the design and the decision‐making of a slope‐based engineering is still not practical to rely solely on the theoretical analysis and numerical calculation, but mainly on the experience of the experts. Therefore, it has important practical significance to turn some successful experience into mathematic equations. Based upon the abundant typical slope engineering construction cases in Yunnan, Southwestern China, 3 methods for analyzing the slope stability have been developed in this paper. First of all, the corresponded analogous mathematic equation for analyzing slope stability has been established through case studies. Then, artificial neural network and multivariate regression analysis have also been set up when 7 main influencing factors are adopted.