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Some Novel Dynamic Fuzzy Sets Models Applied to the Classification of Outsourced Software Project Risk

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International Conference on Oriental Thinking and Fuzzy Logic

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 443))

Abstract

Some novel dynamic fuzzy sets (DFS) models, which are the generalization of fuzzy sets (FS) and the dynamization of interval-valued intuitionistic fuzzy sets (IVIFS), are presented in this paper. First, we propose some weighted DFS models from IVIFS. Second, we introduce the distance formula of DFS. Finally, we apply these DFS models and the distance measures to pattern classification of outsourced software project risk to demonstrate the advantages of these DFS models, and the experimental results show that these DFS models are more effective than the conventional clustering algorithms and IVIFS model in pattern classification.

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Acknowledgements

This paper is funded by the National Natural Science Foundation of China (No. 71271061), the “Twelfth Five-Years” Philosophy and Social Sciences Planning Project of Guangdong Province (No. GD12XGL14), the Science and Technology Innovation Project of Department of Education of Guangdong Province (No. 2013KJCX0072), “Twelfth Five-Years” Philosophy and Social Sciences Planning Project of Guangzhou (No. 14G41), the Natural Science Foundation of Guangdong Province (No. 2014A030313575), the Soft Science Project on Public Research and Capacity Building of Guangdong Province (No. 2015A070704051), the Business Intelligence Key Team of Guangdong University of Foreign Studies (No. TD1202), Student Science and Technology Innovation Cultivating Projects & Climbing Plan Special Key Funds in Guangdong Province (No. 308-GK151011), the Major Education Foundation of Guangdong University of Foreign Studies (No. GYJYZDA14002), the Higher Education Research Project of Guangdong University of Foreign Studies (No. 2016GDJYYJZD004), the National Students Innovation Training Program of China (No. 201511846058).

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Authors and Affiliations

  1. School of Economics and Trade, Guangdong University of Foreign Studies, Guangzhou, 510006, China

    Zhen-hua Zhang, Kui-xi Xiao, Zhi-jun Li & Xiao-xin Chen

  2. Faculty of Business, Environment and Society, Coventry University, Coventry, CV1 5FB, UK

    Zhen-hua Zhang

  3. School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China

    Guo-hua Qu

  4. Institute of Big Data and Decision Making, Jinan University, Guangzhou, 510632, China

    Yong Hu

  5. School of Finance Guangdong University of Foreign Studies, Guangzhou, 510006, China

    Jin-hui Xu & Chao Ma

  6. Department of Statistics, Indiana University, Bloomington, IN47408, USA

    Jin-hui Xu

Authors
  1. Zhen-hua Zhang
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  2. Guo-hua Qu
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  3. Kui-xi Xiao
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  4. Yong Hu
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  5. Zhi-jun Li
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  6. Xiao-xin Chen
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  7. Jin-hui Xu
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  8. Chao Ma
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Correspondence to Zhen-hua Zhang .

Editor information

Editors and Affiliations

  1. Guangzhou Vocational Collg. Sci. & Tech., Guangzhou, China

    Bing-Yuan Cao

  2. West Texas A&M University, Canyon,TX,USA, Liaoning Technical University, Fuxin, China

    Pei-Zhuang Wang

  3. Foreign Affairs Office, National Defense University, Beijing, China

    Zeng-Liang Liu

  4. School of Math and Info. Science, Guangzhou University, Guangzhou, China

    Yu-Bin Zhong

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Zhang, Zh. et al. (2016). Some Novel Dynamic Fuzzy Sets Models Applied to the Classification of Outsourced Software Project Risk. In: Cao, BY., Wang, PZ., Liu, ZL., Zhong, YB. (eds) International Conference on Oriental Thinking and Fuzzy Logic. Advances in Intelligent Systems and Computing, vol 443. Springer, Cham. https://doi.org/10.1007/978-3-319-30874-6_27

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  • DOI: https://doi.org/10.1007/978-3-319-30874-6_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30873-9

  • Online ISBN: 978-3-319-30874-6

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