Comprehensive Models for Evaluating Rockmass Stability Based on Statistical Comparisons of Multiple Classifiers
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-09-12
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
The relationships between geological features and rockmass behaviors under complex geological environments were investigated based on multiple intelligence classifiers.
Random forest, support vector machine, bayes' classifier, fisher's classifier, logistic regression, and neural networks were used to establish models for evaluating the rockmass stability of slope.
Samples of both circular failure mechanism and wedge failure mechanism were considered to establish and calibrate the comprehensive models.
The classification performances of different modeling approaches were analyzed and compared by receiver operating characteristic (ROC) curves systematically.
Results show that the proposed random forest model has the highest accuracy for evaluating slope stability of circular failure mechanism, while the support vector Machine model has the highest accuracy for evaluating slope stability of wedge failure mechanism.
It is demonstrated that the established random forest and the support vector machine models are effective and efficient approaches to evaluate the rockmass stability of slope.
American Psychological Association (APA)
Dong, Longjun& Li, Xibing. 2013. Comprehensive Models for Evaluating Rockmass Stability Based on Statistical Comparisons of Multiple Classifiers. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1009235
Modern Language Association (MLA)
Dong, Longjun& Li, Xibing. Comprehensive Models for Evaluating Rockmass Stability Based on Statistical Comparisons of Multiple Classifiers. Mathematical Problems in Engineering No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-1009235
American Medical Association (AMA)
Dong, Longjun& Li, Xibing. Comprehensive Models for Evaluating Rockmass Stability Based on Statistical Comparisons of Multiple Classifiers. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1009235
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1009235