淡江大學機構典藏:Item 987654321/68620
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 62822/95882 (66%)
造访人次 : 4025230      在线人数 : 1058
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧：
  • 您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果
  • 若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据
    •  进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/68620


    题名: Comparison of regression and neural network models for prediction of inspection profiles for aging aircraft
    作者: Luxhoj, James T.;Williams, Trefor P.;徐煥智;Shyur, Huan-jyh
    贡献者: 淡江大學資訊管理學系
    日期: 1997-02-01
    上传时间: 2011-10-23 13:19:50 (UTC+8)
    摘要: Currently under phase 2 development by the Federal Aviation Administration (FAA), the Safety Performance Analysis System (SPAS) contains ‘alert’ indicators of aircraft safety performance that can signal potential problem areas for inspectors. The Service Difficulty Reporting (SDR) system is one component of SPAS and contains data related to the identification of abnormal, potentially unsafe conditions in aircraft and/or aircraft components/equipment.
    SPAS contains performance indicators to assist safety inspectors in diagnosing an airline's safety ‘profile’ compared with others in the same peer class. This paper details the development of SDR prediction models for the DC-9 aircraft by analyzing sample data from the SDR database that have been merged with aircraft utilization data. Both multiple regression and neural networks are used to create prediction models for the overall number of SDRs and for SDR cracking and corrosion cases. These prediction models establish a range for the number of SDRs outside which safety advisory warnings would be issued. It appears that a data ‘grouping’ strategy to create aircraft ‘profiles’ is very effective at enhancing the predictive accuracy of the models. The results from each competing modeling approach are compared and managerial implications to improve the SDR performance indicator in SPAS are provided.
    關聯: IIE transaction 29(2), pp.91-101
    DOI: 10.1080/07408179708966316
    显示于类别:[資訊管理學系暨研究所] 期刊論文

    文件中的档案:

    档案 大小格式浏览次数
    index.html0KbHTML107检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈