Abstract
Information systems are classified into two classes, namely complete information systems and incomplete information systems. A unified description has been proposed through the concrete analysis of information systems. And based on this conclusion, a new method of decision making has been presented. The theoretical basis of the method is non-optimum theory, and thereby the non-optimum theory is further perfect by introduced the concepts of middle-optimum degree and unknown-optimum degree. Then the entropy of information systems is defined. Meanwhile, the concept of influence degree has also introduced. Finally, it discusses about three decision making principles, namely maximum influence degree principle, minimum risk principle and maximum risk principle.
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References
Zadeh, L.A.: Fuzzy sets. J. of Information and Control 8, 338–353 (1965)
Deng, H.: Multicriteria analysis with fuzzy pairwise comparison. J. App., 215–231 (1999)
Yeh, C.H., Deng, H.: A practical approch to fuzzy utilities comparison in fuzzy multicriteria analysis. Int. J. App., 179–194 (2004)
Ekel, P.Y., Martini, J.S.C., Palhares, R.M.: Multicriteria analysis in decision making under information uncertainty. App. Maths. Comp., 501–516 (2008)
Ribeiro, R.: A Fuzzy multiple attribute decision making:A revirw and new preference elicitation techniques. J. of Fuzzy Sets and Syst. 78, 155–181 (1996)
Deng, H.P.: Developments in fuzzy multicriteria analysis. Fuzz Inf. Eng., 103–109 (2009)
Deng, H., Yeh, C.H.: Simulation-based evalution of defuzzification-based approaches to fuzzy multiattribute decision making. IEEE Trans. Syst., Man, Cybern., 968–977 (2006)
Roy, B.: Multicriteria Methodology for Decision Aiding. Kluwer, Dordrecht (1996)
He, P.: Non-optimum system theory and methods. In: First Joint IFSA-EC Workshop (1986)
He, P.: System Non-optimum Analysis Theory and Method. J. of Engineering Science 5(7), 40–46 (2003)
He, P.: Theories and methods of non-optimum analysis on systems. J. of Engineering Sciences 2, 73–80 (2004)
He, P.: System non-optimum analysis and extension optimum theory. J. of Systems Science and Systems Engineering, ICSS 2003, 131–137 (2003)
Duan, L.H., He, P.: Synthetic Assessment System Based on Non-optimum Analysis Theory. In: International Conference Research Challenges in Computer Science, ICRCCS, pp. 133–136 (2009)
Rady, E.A., Abd El-Monsef, M.M.E., Abd El-Latif, W.A.: A Modified Rough Set Approach to Incomplete Information Systems. J. of Applied Mathematics and Decision Sciences, Article ID 58248, 1–13 (2007)
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Duan, L., He, P. (2010). Non-optimum Analysis Approach to Incomplete Information Systems. In: Cao, By., Wang, Gj., Guo, Sz., Chen, Sl. (eds) Fuzzy Information and Engineering 2010. Advances in Intelligent and Soft Computing, vol 78. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14880-4_55
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DOI: https://doi.org/10.1007/978-3-642-14880-4_55
Publisher Name: Springer, Berlin, Heidelberg
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