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    政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 >  Item 140.119/73507
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/73507

    Title: A new approach to applying feedforward neural networks to the prediction of musculoskeletal disorder risk
    Authors: 陳春龍
    DB, Kaber;PG, Dempsey;Chen, Chun-Lung
    Contributors: 資管系
    Date: 2000-01
    Issue Date: 2015-02-12 14:44:57 (UTC+8)
    Abstract: A new and improved method to feedforward neural network (FNN) development for application to data classification problems, such as the prediction of levels of low-back disorder (LBD) risk associated with industrial jobs, is presented. Background on FNN development for data classification is provided along with discussions of previous research and neighborhood (local) solution search methods for hard combinatorial problems. An analytical study is presented which compared prediction accuracy of a FNN based on an error-back propagation (EBP) algorithm with the accuracy of a FNN developed by considering results of local solution search (simulated annealing) for classifying industrial jobs as posing low or high risk for LBDs. The comparison demonstrated superior performance of the FNN generated using the new method. The architecture of this FNN included fewer input (predictor) variables and hidden neurons than the FNN developed based on the EBP algorithm. Independent variable selection methods and the phenomenon of 'overfitting' in FNN (and statistical model) generation for data classification are discussed. The results are supportive of the use of the new approach to FNN development for applications to musculoskeletal disorders and risk forecasting in other domains.
    Relation: Applied Ergonomics,31,269-282
    PMID: 10855450
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1016/S0003-6870(99)00055-1
    DOI: 10.1016/S0003-6870(99)00055-1
    Appears in Collections:[資訊管理學系] 期刊論文

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