An intelligent decision support model for aviation weather forcasting

Sergio Viademonte, Frada V Burstein

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    3 Citations (Scopus)


    Ability to collect and utilize historical data is very important for efficient decision support. On the other hand this data often requires significant pre-processing and analysis in order to bring any value for the user-decision-maker. Knowledge Discovery in Databases (KDD) can be used for these purposes in exploiting massive data sets. This paper describes a computational architecture for decision support system, which comprises an artificial neural network component for the KDD purposes. It integrates mining data set stored in databases, knowledge base produced by data mining and artificial neural network components, which serve the role of an intelligent interface for producing recommendations for decision-maker. The architecture is being implemented in the context of aviation weather forecasting. The proposed architecture can serve as a model for a KDD-based intelligent decision support for any complex decision situations where large volume of historical data is available.

    Original languageEnglish
    Title of host publicationAdvances in Intelligent Data Analysis
    Subtitle of host publication4th International Conference, IDA 2001 Cascais, Portugal, September 13-15, 2001 Proceedings
    EditorsFrank Hoffmann, David J. Hand, Niall Adams, Douglas Fisher, Gabriela Guimaraes
    Place of PublicationBerlin Germany
    Number of pages11
    ISBN (Print)3540425810, 9783540425816
    Publication statusPublished - 2001
    Event4th International Conference on Intelligent Data Analysis, IDA 2001 - Cascais, Portugal
    Duration: 13 Sep 200115 Sep 2001

    Publication series

    NameLecture Notes in Computer Science
    ISSN (Print)0302-9743


    Conference4th International Conference on Intelligent Data Analysis, IDA 2001

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