Methodological Principles of Uncertainty in Information Systems Modeling

作者: George J. Klir

DOI: 10.1007/978-1-4684-5862-6_4

关键词:

摘要: System modeling permeates all disciplines of science, both natural and artificial. The general concepts system are presented in summary fashion. key role uncertainty is discussed including the principles maximum minimum uncertainty. Recent results regarding conceptualization uncertainty, which demonstrate that a multidimensional concept, overviewed, implications for information software engineering discussed.

参考文章(36)
John Skilling, Theory of Maximum Entropy Image Reconstruction Cambridge University Press. pp. 156- 178 ,(1986) , 10.1017/CBO9780511569678.011
M. Umano, Retrieval From Fuzzy Database by Fuzzy Relational Algebra IFAC Proceedings Volumes. ,vol. 16, pp. 1- 6 ,(1983) , 10.1016/S1474-6670(17)61995-5
Abraham Kandel, Lawrence O'Higgins Hall, Designing fuzzy expert systems TÜV Rheinland. ,(1986)
Madan M. Gupta, Approximate reasoning in expert systems North-Holland. ,(1985)
Ronald R. Yager, Lotfi Asker Zadeh, Fuzzy sets and applications : selected papers Wiley. ,(1987)
R. V. L. Hartley, Transmission of Information1 Bell System Technical Journal. ,vol. 7, pp. 535- 563 ,(1928) , 10.1002/J.1538-7305.1928.TB01236.X
George J. Klir, Tina A. Folger, Fuzzy Sets, Uncertainty and Information ,(1988)
A. Wayne Wymore, A mathematical theory of systems engineering--the elements R.E. Krieger Pub. Co.. ,(1967)
Mihajlo D Mesarovic, Yasuhiko Takahara, General Systems Theory: Mathematical Foundations ,(1975)
George J. Klir, Doug Elias, Architecture of Systems Problem Solving ,(2011)