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Issue title: Recent advancements in computer, communication and computational sciences
Guest editors: K.K. Mishra
Article type: Research Article
Authors: Zhang, Zhenhuaa; * | Hu, Yongb | Ma, Chaoc | Xu, Jinhuid | Yuan, Shenguoa | Chen, Zhaoa
Affiliations: [a] School of Economics and Trade, Guangdong University of Foreign Studies, Guangzhou, China | [b] Institute of Big Data and Decision Making, Jinan University, Guangzhou, China | [c] Department of Computer Science, University College London, Gower Street, London, UK | [d] Department of Statistics, Indiana University Bloomington, Indiana Avenue Bloomington, IN, USA
Correspondence: [*] Corresponding author. Zhenhua Zhang, Ph.D., School of Economics and Trade, Guangdong University of Foreign Studies, Guangzhou 510006, China. Tel.: +86 13660061726; Fax: +86 2039328096; E-mail: zhangzhenhua@gdufs.edu.cn.
Abstract: By analyzing three parts of interval valued intuition fuzzy sets (IVIFS), we provide a novel framework constructing risk function with IVIFS information for risk analysis of outsourced software project. First, we introduced some risk factors of outsourced software project according to their hierarchical levels, and present a general risk function model. And then, some useful mathematical properties of this risk function are proved. Based on the mathematical properties of general risk function, all these presented specific risk functions are classified into four types: incentive function, punitive function, incentive-punitive function and equilibrium function. Especially, two kinds of incentive-punitive risk functions are focused on and a construction method for them is proposed. Finally, an application example for the risk assessment of outsourced software project illustrates the use of this decision making method. The simulation results show that these functions are effective in risk prediction.
Keywords: Interval valued intuitionistic fuzzy sets, risk assessment, incentive-punitive risk function, equilibrium risk function, outsourced software project
DOI: 10.3233/JIFS-169307
Journal: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 5, pp. 3749-3760, 2017
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