SHS Web of Conferences
Volume 25, 2016ICITCE 2015 – 3rd International Conference on Information Technology and Career Education
|Number of page(s)||7|
|Section||Economy and technology|
|Published online||22 April 2016|
- Kahraman, C. & Cebi, S. 2009. A new multi-attribute decision making method: Hierarchical fuzzy axiomatic design. Expert Systems with Applications. 36: 4848–4861. [CrossRef]
- Chen, T. 2012. Multiple criteria group decision-making with generalized interval-valued fuzzy numbers based on signed distances and incomplete weights. Applied Mathematical Modelling, 36: 3029–3052. [CrossRef]
- Z.S. Xu & J. Chen. 2007. An interactive method for fuzzy multiple attributes group decision making. Inform Sciences, 177: 248–263. [CrossRef]
- Z.J. Wang, K.W. Li & W.Z. Wang. 2009. An approach to multiple attribute decision making with interval-valued intuitionistic fuzzy assessments and incomplete weights. Inform Sciences, 179: 3026–3040. [CrossRef]
- J. Ye. 2010. Fuzzy decision-making method based on the weighted correlation coefficient under intuitionistic fuzzy environment. Eur J Oper Res, 205: 202–204. [CrossRef]
- G.W. Wei. 2010. Extension of TOPSIS method for 2-tuple linguistic multiple attribute group decision making with incomplete weight information. Know Inf Syst, 25: 623–634. [CrossRef]
- D. Molodtsov. 1999. Soft set theory-first results. Comput Math Appl, 37: 19–31. [CrossRef]
- P.K. Maji & A.R. Roy. 2002. An application of soft sets in a decision making problem. Comput Math Appl, 44: 1077–1083. [CrossRef]
- M.M. Mushrif, S. Sengupta & A.K. Ray. 2006. Texture classification using a novel, soft-set theory based classification algorithm. COMPUTER VISION-ACCV 2006, pp.246–254. [CrossRef]
- Y. Zou & Z. Xiao. 2008. Data analysis approaches of soft sets under incomplete information. Knowl-Based Syst, 21: 941–945. [CrossRef]
- A.R. Roy & P.K. Maji. 2007. A fuzzy soft set theoretic approach to decision making problems. J Comput Appl Math, 203: 412–418. [CrossRef]
- Z. Kong, L.Q. Gao & L.F. Wang. 2009. Comment on “A fuzzy soft set theoretic approach to decision making problems”. J Comput Appl Math, 223: 540–542. [CrossRef]
- N. Cagman & S. Enginoglu. 2010. Soft set theory and uni-int decision making. Eur J Oper Res, 207: 848–855. [CrossRef]
- F. Feng, Y.B. Jun, X. Liu & L. Li. 2010. An adjustable approach to fuzzy soft set based decision making. J Comput Appl Math, 234: 10–20. [CrossRef]
- S.J. Chen & C.L. Hwang. 1992. Fuzzy Multiple Attribute Decision Making: Method and Applications, New York: Springer-Verlag.
- T.L. Saaty. 1996. Decision Making with Dependence and Feedback: The Analytic Network Process: The Organization and Priorization of Complexity. Pittsburgh: RWS Publications.
- T.L. Saaty & L.G. Vargas. 1998. Diagnosis with dependent symptoms: Bayes theorem and the analytic hierarchy process. Oper Res, 46: 491–502. [CrossRef]
- R. Yua & G. Tzeng. 2006. A soft computing method for multi-criteria decision making with dependence and feedback. Appl Math Computation, 180: 63–75. [CrossRef]
- B. Kosko. 1996. Fuzzy Engineering, New York: Prentice Hall.
- Z. Xu. 2007. A method for multiple attribute decision making with incomplete weight information in linguistic setting. Knowl-Based Syst, 20: 719–725. [CrossRef]
- D. Park, Y. Kwun, J. Park & I. Park. 2009. Correlation coefficient of interval-valued intuitionistic fuzzy sets and its application to multiple attribute group decision making problems. Math Comput Model, 50: 1279–1293. [CrossRef]
- S. French, R. Hartley, L.C. Thomas & D.J. White. 1983. Multi-objective Decision Making, New York: Academic Press.
- Y.T. Lin et al. 2010. A novel hybrid MCDM approach for outsourcing vendor selection: A case study for a semiconductor company in Taiwan. Expert Syst Appl, 37: 4796–4804. [CrossRef]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.