Research on project risk assessment model based on data mining and case-based reasoning

Li Wei Zhang*, Xue Feng Wang, Dong Hua Zhu

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    For the project risk prediction is even more difficult in complicated market environment, the project risk assessment based on the prediction is most difficult and time-consuming in the management. It is speedily researched that how to use the previous completed projects to help new projects avoid the risks. Therefore, a model of projects risk assessment system based on integrating data mining (DM) and case-based reasoning (CBR) was suggested, in which the former is used for the discovery of risk rules, the latter for the use of implicit knowledge. It is the main processes of evaluating the project risk, adopting data mining techniques to discover the implicit meaningful rules from project risk cases; using and evaluating the extracted rules; employing CBR to support the project risk assessment; learning cases and rules, and expanding case database and rule database. The preliminary experiment finds that the model improves the veracity and speed of project risk assessment, and the assessment result is more practical.

    Original languageEnglish
    Pages (from-to)76-79
    Number of pages4
    JournalBinggong Xuebao/Acta Armamentarii
    Volume29
    Issue numberSUPPL.
    Publication statusPublished - Nov 2008

    Keywords

    • Case-based reasoning
    • Data mining
    • Management engineering
    • Project risk assessment

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