A Fuzzy TOPSIS Approach for Big Data Analytics Platform Selection

Subject Areas : Fuzzy Systems

Salah  Uddin ¹ (Multimedia & Creative Technology, Daffodil International University)
Mizanur  Rahman ² (Department of Multimedia and Creative Technology, Daffodil International University, Dhaka, Bangladesh)
Samaun  Hasan ³ (Department of Multimedia and Creative Technology, Daffodil International University, Dhaka, Bangladesh)
S.M. Irfan  Rana ⁴ (Department of Multimedia and Creative Technology, Daffodil International University, Dhaka, Bangladesh)
Shaikh Muhammad  Allayear ⁵ (Department of Multimedia and Creative Technology, Daffodil International University, Dhaka, Bangladesh)

Received: 2018-12-23 Accepted : 2019-01-24 Published : 2019-02-01

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References:

[1] Saecker, M., & Markl, V. (2. Big Data Analytics on Modern Hardware Architectures: A Technology Survey. In M. A. Aufaure & E. Zimányi (Eds.), Business Intelligence (pp. 125-149). Berlin Heidelberg: Springer..
[2] Elgendy, N., & Elragal, A. (2014). Big Data Analytics: A Literature Review Paper. In P. Perner (Ed.), ICDM 2014. LNAI, vol. 8557 (pp. 214-227). Heidelberg: Springer..
[3] Lněnička, M., & Komárková, J. . An Overview and Comparison of Big Data Analytics Platforms. In Sborník příspěvků z mezinárodní vědecké konference MMK 2014 (pp. 3446-3455). Hradec Králové: Magnanimitas.
[4] TIEN-CHIN WANG, HSIEN-DA LEE and CHUAN-CHENG WU. A Fuzzy TOPSIS Approach with Subjective Weights and Objective Weights.
[5] Mohammad Dabbagh, S.P.L. (2014) An Approach for Integrating the Prioritization of Functional and Nonfunctional Requirements. The Scientic World Journal, 2014, Article ID: 737626.
[6] Arfan Mansoor, Detlef Streitferdt, Franz-Felix Füßl. Alternatives Selection Using GORE Based on Fuzzy Numbers and TOPSIS.
[7] Chen-Tung, Ch., "Extensions of the TOPSIS for group decision-making under fuzzy environment",Fuzzy Sets and Systems, Volume 114, 2000.
[8] S. J. Chen and C. L. Hwang, Fuzzy Multiple Attribute Decision Making, (Lecture Notes in Economics and Mathematical System Series 375).Springer-Verlag. New York, 1992.
[9] C.-B. Cheng, 2004. Group Opinion Aggregation Based on a Grading Process: A Method for Constructing Triangular Fuzzy Numbers. Computers and Mathematics with Applications 48:1619-1632.
[10] D. Dubois and H. Prade. 1980. Fuzzy Sets and Systems: Theory and Applications. Academic Press, New York, 393 pp.
[11] C. Elkan, 1994. The Paradoxical Success of Fuzzy Logic. IEEE Expert: Intelligent Systems and Their Applications, 9(4):3-8.
[12] A. Kaufman, and M.M. Gupta. 1991. Introduction to Fuzzy Arithmetic, Theory and Application. Van Nostrand Reinhold Company, New York, 351 pp.