NDLI: Grouting Stratum Classification with Support Vector Machines

Content Provider	IEEE Xplore Digital Library
Author	Fengling Li Zhixiang Hou Quntai Shen Lisheng Xu
Copyright Year	2008
Description	Author affiliation: Center for Controlling & Meas., Changsha Univ. of Sci. & Technol., Changsha (Fengling Li; Zhixiang Hou; Quntai Shen) \|\| Center for Control Theor. & Eng., Central South Univ., Changsha (Lisheng Xu)
Abstract	A support vector machines (SVM) approach is proposed for grout stratum identification based on the grout instrument measurement datum in the grouting consolidation project. The important features of SVM model are obtained by analysis of grout fluid penetration mechanism integrating with grout physical model for pressure control aim. Then we introduce Lagrange multiplier and translate the SVM math model into an unconstrained objective function. The optimal hyper-planes is produced by quadratic programming technics and RBF kernel. In the real grouting project, we draw the osmosis-flow character curves in the different stratum by test , which are major grout parameters changing with stratum. And we obtain the primal datum of SVM classification. At last ,we separately choose 49 group datum for fracture vein rock and gritstone stratum. A part of them is used to training set of SVM ,the other is used to check up the classification effect. Simulations demonstrate identification error is less than 6.13%, so the method can applied to the automatic grout project.
Starting Page	195
Ending Page	199
File Size	306271
Page Count	5
File Format	PDF
ISBN	9780769533575
DOI	10.1109/ICICTA.2008.242
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Geology Instruments Educational institutions Pressure control SVM Face detection Automotive engineering stratum Support vector machines identification Support vector machine classification Geologic measurements Testing
Content Type	Text
Resource Type	Article

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2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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