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A Review of Advances in Extreme Learning Machine Techniques and Its Applications

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Recent Trends in Information and Communication Technology (IRICT 2017)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 5))

Abstract

Feedforward neural networks (FFNN) has been used for machine learning researches, and it really has a wide acceptance. It was noted in the recent time that feedforward neural network is far slower than required. This has created a serious bottleneck in its applications. Extreme Learning Machines (ELM) had been proposed as alternative learning algorithm to FFNN, which is characterized by single-hidden layer feedforward neural networks (SLFN). It randomly chooses hidden nodes and determines their output weight analytically. This paper review is to provide a roadmap for ELM as an efficient research tool in machine learning with the aim of finding research gap into further study. It was discovered through this study that research publications in ELM continues to grow yearly from 16.20% in 2013 to 40.83% in 2016.

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Acknowledgements

The authors wish to thank Universiti Teknologi Malaysia (UTM) under Research University Grant Vot-02G31 & Vot-15H17 and Ministry of Higher Education Malaysia (MOHE) under the Fundamental Research Grant Scheme (FRGS Vot-4F551) for the completion of the research.

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Authors and Affiliations

  1. Faculty of Computing, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia

    Oyekale Abel Alade, Ali Selamat & Roselina Sallehuddin

  2. Computer Science Department, Federal Polytechnic, Bida, Nigeria

    Oyekale Abel Alade

Authors
  1. Oyekale Abel Alade
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  2. Ali Selamat
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  3. Roselina Sallehuddin
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Corresponding author

Correspondence to Ali Selamat .

Editor information

Editors and Affiliations

  1. Faculty of Computing Information Systems Department, Universiti Teknologi Malaysia, Johar, Skudai, Malaysia

    Faisal Saeed

  2. Faculty of Computing Information Systems Department, Universiti Teknologi Malaysia, Johar, Skudai, Malaysia

    Nadhmi Gazem

  3. Department of Computer Science and Engineering, SOA University, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  4. Faculty of Computing, ISSI Research Lab, University of Technology Malaysia, Skudai, Malaysia

    Ali Saleh Saed Balaid

  5. Faculty of Computing, University of Technology Malaysia, Skudai, Malaysia

    Fathey Mohammed

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Alade, O.A., Selamat, A., Sallehuddin, R. (2018). A Review of Advances in Extreme Learning Machine Techniques and Its Applications. In: Saeed, F., Gazem, N., Patnaik, S., Saed Balaid, A., Mohammed, F. (eds) Recent Trends in Information and Communication Technology. IRICT 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-59427-9_91

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  • DOI: https://doi.org/10.1007/978-3-319-59427-9_91

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59426-2

  • Online ISBN: 978-3-319-59427-9

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