International Journal of
Computer Sciences and Engineering

Scholarly Peer-Reviewed, and Fully Refereed Scientific Research Journal
A Modified Fuzzy Similarity Measure Decision Making Approach to SLCM Selection
A Modified Fuzzy Similarity Measure Decision Making Approach to SLCM Selection
S. J. Kalayathankal1 , J. T. Abraham2 , J. V. Kureethara3
1 Research and Development Centre, Bharathiar University, Coimbatore, India.
2 Department of Computer Science, Bharatha Matha College, Cochin, India.
3 Department of Mathematics and Statistics, Christ University, Bangalore, India.
Correspondence should be addressed to: sunnyjoseph2014@yahoo.com.

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-9 , Page no. 32-39, Sep-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i9.3239

Online published on Sep 30, 2017

Copyright © S. J. Kalayathankal, J. T. Abraham, J. V. Kureethara . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 
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IEEE Style Citation: S. J. Kalayathankal, J. T. Abraham, J. V. Kureethara, “A Modified Fuzzy Similarity Measure Decision Making Approach to SLCM Selection”, International Journal of Computer Sciences and Engineering, Vol.5, Issue.9, pp.32-39, 2017.

MLA Style Citation: S. J. Kalayathankal, J. T. Abraham, J. V. Kureethara "A Modified Fuzzy Similarity Measure Decision Making Approach to SLCM Selection." International Journal of Computer Sciences and Engineering 5.9 (2017): 32-39.

APA Style Citation: S. J. Kalayathankal, J. T. Abraham, J. V. Kureethara, (2017). A Modified Fuzzy Similarity Measure Decision Making Approach to SLCM Selection. International Journal of Computer Sciences and Engineering, 5(9), 32-39.
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Abstract :
Software engineering has been largely looked upon as a layered technology that integrates processes, people and technology for the software development. The choice of one particular model over a set of available models will depend on its efficacy and appropriateness. The ultimate goal of any form of software engineering is to build up the most efficient model and this build up will decide the future and successful completion of any project. The study intends to develop similarity measures between ordered intuitionistic fuzzy soft sets (OIFSSs). The proposed model is applied to five software life cycle models (SLCMs) so as to select the most appropriate one.
Key-Words / Index Term :
Similarity measure, Software life cycle, Fuzzy decision making, Intuitionistic fuzzy soft sets
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