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      Hybrid Grey Wolf Optimization Algorithm–Based Support Vector Machine for Groutability Prediction of Fractured Rock Mass

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          Grey Wolf Optimizer

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            LIBSVM: A library for support vector machines

            LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM to their applications. LIBSVM has gained wide popularity in machine learning and many other areas. In this article, we present all implementation details of LIBSVM. Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.
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              The Nature of Statistical Learning Theory

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                Author and article information

                Journal
                Journal of Computing in Civil Engineering
                J. Comput. Civ. Eng.
                American Society of Civil Engineers (ASCE)
                0887-3801
                1943-5487
                March 2019
                March 2019
                : 33
                : 2
                Affiliations
                [1 ]Ph.D. Candidate, State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin Univ., Tianjin 300072, China.
                [2 ]Professor, State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin Univ., Tianjin 300072, China (corresponding author).
                Article
                10.1061/(ASCE)CP.1943-5487.0000814
                77275146-c24c-4827-b3b6-f4add241f2e0
                © 2019
                History

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