Griffith Research Online

Griffith Research Online (GRO) is a digital archive of research and scholarship from Griffith University, Brisbane, Australia.

GRO delivers free online full-text versions of journal articles, conference papers, and more, where this is possible with the appropriate permissions of copyright owners. GRO increases the impact and influence of Griffith research and scholarship by ensuring it is visible, discoverable and accessible via search engines like Google and discovery services like the National Library’s Trove.

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Recently Added

  • Whale optimization approaches for wrapper feature selection 

    Mafarja, Majdi M.; Mirjalili, Seyedali (Applied Soft Computing, 2018)
    Classification accuracy highly dependents on the nature of the features in a dataset which may contain irrelevant or redundant data. The main aim of feature selection is to eliminate these types of features to enhance the ...
    JOURNAL ARTICLE

  • Temporary migration of Cambodians into Thailand: A study of repatriated workers in Siem Reap 

    Fraser, Campbell; Howard, Paul (South-South Migration: Emerging Patterns, Opportunities and Risks, 2017)
    This chapter reports on the findings of interviews with 247 Cambodian temporary labour migrants upon repatriation from Thailand. The chapter first discusses the socio-political context that has created the conditions that ...
    BOOK CHAPTER

  • Binary Dragonfly Algorithm for Feature Selection 

    Mafarja, Majdi M.; Eleyan, Derar; Jaber, Iyad; Mirjalili, Seyedali; Hammouri, Abdelaziz (ICTCS 2017, 2017)
    Wrapper feature selection methods aim to reduce the number of features from the original feature set to and improve the classification accuracy simultaneously. In this paper, a wrapper-feature selection algorithm based on ...
    CONFERENCE OUTPUT

  • Autonomous Particles Groups for Particle Swarm Optimization 

    Mirjalili, Seyedali; Lewis, Andrew; Sadiq, Ali Safa (Arabian Journal for Science and Engineering, 2014)
    In this paper, a modified particle swarm optimization (PSO) algorithm called autonomous groups particles swarm optimization (AGPSO) is proposed to further alleviate the two problems of trapping in local minima and slow ...
    JOURNAL ARTICLE

  • Development in Jinghong, Xishuangbanna: 1990-2012 

    Howard, Paul (International Journal of Development Management, 2014)
    JOURNAL ARTICLE

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