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      Dempster-Shafer evidence theory for multi-bearing faults diagnosis

      , , ,
      Engineering Applications of Artificial Intelligence
      Elsevier BV

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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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            Bearing fault detection of induction motor using wavelet and Support Vector Machines (SVMs)

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              Multi-fault classification based on wavelet SVM with PSO algorithm to analyze vibration signals from rolling element bearings

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                Author and article information

                Journal
                Engineering Applications of Artificial Intelligence
                Engineering Applications of Artificial Intelligence
                Elsevier BV
                09521976
                January 2017
                January 2017
                : 57
                : 160-170
                Article
                10.1016/j.engappai.2016.10.017
                fcc2c8fe-570e-47dc-9c17-bd3699e3dd19
                © 2017

                https://www.elsevier.com/tdm/userlicense/1.0/

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