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    An integrated data envelopment analysis – artificial neural network – rough set algorithm for assessment of personnel efficiency

    Access Status
    Fulltext not available
    Authors
    Azadeh, A.
    Saberi, Morteza
    Moghaddam, R.
    Javanmardi, L.
    Date
    2011
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Azadeh, A. and Saberi, M. and Moghaddam, R. and Javanmardi, L. 2011. An integrated data envelopment analysis – artificial neural network – rough set algorithm for assessment of personnel efficiency. Expert Systems with Applications. 38 (3): pp. 1364-1373.
    Source Title
    Expert Systems with Applications
    Additional URLs
    http://www.sciencedirect.com/science/article/pii/S0957417410006615
    ISSN
    0957-4174
    School
    Digital Ecosystems and Business Intelligence Institute (DEBII)
    URI
    http://hdl.handle.net/20.500.11937/49767
    Collection
    • Curtin Research Publications
    Abstract

    Personnel specifications have greatest impact on total efficiency. They can help us to design work environment and enhance total efficiency. Determination of critical personnel attributes is a useful procedure to overcome complication associated with multiple inputs and outputs. The proposed algorithm assesses the impact of personnel efficiency attributes on total efficiency through Data Envelopment Analysis (DEA), Artificial Neural Network (ANN) and Rough Set Theory (RST). DEA has two roles in the proposed integrated algorithm of this study. It provides data ANN and finally it selects the best reduct through ANN result. Reduct is described as a minimum subset of attributes, completely discriminating all objects in a data set. The reduct selection is achieved by RST. ANN has two roles in the integrated algorithm. ANN results are basis for selecting the best reduct and it is also used for forecasting total efficiency. The proposed integrated approach is applied to an actual banking system and its superiorities and advantages are discussed.

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