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• W2023631707 abstract "Delivering accurate software effort estimation has been a research challenge for a long time, where none of the existing estimation methods has proven to consistently deliver an accurate estimate. Previous studies have demonstrated that estimation by analogy (EBA) is a viable alternative to other conventional estimation methods in terms of predictive accuracy. EBA offers a way to use a formal method with data from a past project to derive a new estimate. Two important research areas in EBA are addressed in this paper: software projects similarity measurement and attribute weighting. However, the inherent uncertainty of attribute measurement makes similarity measurement between two software projects subject to considerable uncertainty. To tolerate such inherent uncertainty we propose a new similarity measurement method by combining the advantages of Fuzzy Set Theory and Grey Relational Analysis. In addition, since each attribute has different influence on the project retrieval we propose a new approach to deal with this issue based upon the idea of Kendall's coefficient of concordance between the similarity matrix of project attributes and the similarity matrix of known effort values of the dataset. Our results show improved prediction accuracy when multiple project attributes are used with determined weights." @default.
• W2023631707 created "2016-06-24" @default.
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• W2023631707 date "2009-05-18" @default.
• W2023631707 modified "2023-09-24" @default.
• W2023631707 title "Software effort estimation based on weighted fuzzy grey relational analysis" @default.
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• W2023631707 doi "https://doi.org/10.1145/1540438.1540450" @default.
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