@article{MAKHILLAJIT2004354710,
    title = {Classifying Plant Operator Productivity Using Computational Science},
    journal = {Asian Journal of Information Technology},
    volume = {3},
    number = {5},
    pages = {336-346},
    year = {2004},
    issn = {1682-3915},
    doi = {ajit.2004.336.346},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2004.336.346},
    author = {Junli Yang,David J. Edwards and},
    keywords = {},
    abstract = {This paper presents a conceptual model with which to classify plant operator productivity using the artificial intelligent technique, neural networks (ANN). Specially, an artificial network model is proposed that uses factors such as: operator`s motivation, management role, maintenance task taken, stress and fatigue, education and training. Within these broad ‘generic` factors, a comprehensive range of variables exist. The ANN system design proposes a feed-forward multiplayer perceptron with back-propagation algorithm that will predict three levels of operator` productivity (namely high, medium and low). It is then proposed that the maths and algorithms developed be incorporated into a web-based software solution that connects databases of information, held on a server with dual connectivity capabilities, to users using Active Server Pages (ASP) programming code. Using this approach, it is anticipated that a user-friendly package will be developed that will enable the widest possible practitioner audience to access the software, anywhere on the planet, anytime of day.}
    }