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A Method for Knowledge Checking Service Selection with Incomplete Weight Information Based on the Grey Related Analysis and Data Envelopment Analysis in Fuzzy Environment

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 393))

Abstract

The knowledge checking service (KCS) is critical for safeguarding the quality of knowledge. In organizations, there are many knowledge checking services with similar functions but different qualities, in order to select the best KCS, the method which combines grey related analysis (GRA) with data envelope analyzes (DEA) with incomplete weight information in fuzzy environment is proposed. In the method, the evaluation information is given linguistically and processed by the 2-tuple linguistic model and GRA. The DEA model is constructed to derive the precise weight information. Afterwards, by solving DEA model, the order of the alternatives can be derived. In the method, the combination of the advantages of DEA and grey correlation analysis leads to the avoidance of subjectivity and make the selection more accurately. The applicability of the proposed method is validated by an example.

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Acknowledgments

The research is supported by the National Natural Science Foundation of China under Grant No. 71101153, 71301152, 71571191 and Science Foundation of China University of Petroleum, Beijing (No. 2462015YQ0722), Humanity and Social Science Youth Foundation of Ministry of Education in China (Project No. 15YJCZH081, 13YJC790112)

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Correspondence to Yingcheng Xu .

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© 2016 Springer Science+Business Media Singapore

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Li, M., Yu, Y., Xu, Y. (2016). A Method for Knowledge Checking Service Selection with Incomplete Weight Information Based on the Grey Related Analysis and Data Envelopment Analysis in Fuzzy Environment. In: Park, J., Jin, H., Jeong, YS., Khan, M. (eds) Advanced Multimedia and Ubiquitous Engineering. Lecture Notes in Electrical Engineering, vol 393. Springer, Singapore. https://doi.org/10.1007/978-981-10-1536-6_13

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  • DOI: https://doi.org/10.1007/978-981-10-1536-6_13

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-1535-9

  • Online ISBN: 978-981-10-1536-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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