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DC Field | Value | Language |
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dc.contributor.author | Tan, C.H. | |
dc.contributor.author | Yap, K.S. | |
dc.contributor.author | Ishibuchi, H. | |
dc.contributor.author | Nojima, Y. | |
dc.contributor.author | Yap, H.J. | |
dc.date.accessioned | 2018-02-21T04:41:57Z | - |
dc.date.available | 2018-02-21T04:41:57Z | - |
dc.date.issued | 2014 | |
dc.identifier.uri | http://dspace.uniten.edu.my/jspui/handle/123456789/8896 | - |
dc.description.abstract | Expert judgment is widely used for activity duration estimation in software project management. While there are both advantages and disadvantages of expert judgment-based estimation, we propose the use of fuzzy inference rules for semi-automatic estimation to reduce the potential negative aspects of the expert judgment-based estimation. Fourteen fuzzy inference rules are introduced to elicit and adjust expert tacit knowledge, and expert judgment-based estimation results are complemented by fuzzy inference rules. The results from expert judgment and fuzzy inference rules are compared with the expert judgment-based approach using surveys and one-on-one interviews with project managers from different disciplines through analyses with data from past software projects. The use of fuzzy inference rules improves the estimation accuracy of the expert judgment-based approach by 39.35%. The proposed approach facilitates the experts to derive a more realistic and reliable activity duration estimation in software project management. © 2014 IEEE. | |
dc.title | Application of fuzzy inference rules to early semi-automatic estimation of activity duration in software project management | |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
Appears in Collections: | COE Scholarly Publication |
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