政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/100317
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 109952/140891 (78%)
Visitors : 46251453      Online Users : 1254
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/100317


    Title: Data Management Issues and Data Mining of Real Time System Application for Environment Monitoring
    Authors: Saini, Dinesh Kumar;Maskari, Sanad Al
    Keywords: Data Management;Real Time Systems;Data Mining;Environment Monitoring Systems
    Date: 2014-09
    Issue Date: 2016-08-16 16:22:22 (UTC+8)
    Abstract: Environment pollution monitoring and control is very big problem for the whole world. Taking decision in the environment is becoming more challenging. The aim of this paper is to present the challenges surrounding environmental data sets and to address these in order to develop solutions. Environmental data sets present a number of data management challenges including data collection, integration, quality and data mining. Environment data sets are also very dynamic and this presents additional challenges ranging from data gathering to data integration, particularly as these data sets are normally very large and expanding continuously. Statistical methods are very effective and economical way to analyze small, static data sets but they are not applicable for dynamic, real-time and large data sets. The use of data mining methods to discover hidden knowledge in large datasets therefore presents great potential to improve environmental management decisions. A representative environmental data set from quantitative air quality monitoring instruments has been assessed and will be used to demonstrate some of the issues in applying data mining approaches to poor data quality.
    Relation: 資管評論, 20(1), 31-43
    MIS review
    Data Type: article
    DOI link: http://dx.doi.org/10.6131/MISR.2014.2001.02
    DOI: 10.6131/MISR.2014.2001.02
    Appears in Collections:[MIS review: an international journal] Journal Articles

    Files in This Item:

    File Description SizeFormat
    20(1)-31-43.pdf507KbAdobe PDF2672View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback