Research on Two-Stage Model of Project Risk Assessment Based on Knowledge Discovery

DOI

10.2991/isci-15.2015.186How to use a DOI?

Keywords

project risk assessment; data mining; case-based reasoning

Abstract

Risk assessment is the most difficult and most time-consuming process of project risk management. In the complex and volatile market environment, the project risk is more difficult to predict. Although numerous projects which have been completed provide much valuable knowledge for reference, it has not been put into good use. Thus, it is urgent to study how to apply the completed projects to help new projects avoid risks effectively. Therefore, this paper proposes the two-stage model of project risk assessment, in which decision tree is applied for discovering the risk rules at the first stage, and case-based reasoning for utilizing the tacit knowledge at the second stage. The model consists of the following four parts: (1) to explore risks and association rules from the project risk cases by using decision tree technology; (2) to use and evaluate rules; (3) to obtain assessment results by using case-based reasoning method; (4) to extend case base and rule base through case study and rule learning. The preliminary tests show that the model can assess project risks more quickly and accurately and the assessment results are accurate and viable.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Liwei Zhang
AU  - Dandan Zhao
PY  - 2015/01
DA  - 2015/01
TI  - Research on Two-Stage Model of Project Risk Assessment Based on Knowledge Discovery
BT  - Proceedings of the 2015 International Symposium on Computers & Informatics
PB  - Atlantis Press
SP  - 1398
EP  - 1404
SN  - 2352-538X
UR  - https://doi.org/10.2991/isci-15.2015.186
DO  - 10.2991/isci-15.2015.186
ID  - Zhang2015/01
ER  -