Abstract
Soft Computer-Aided System Theory and Technology or SCAST is introduced as a branch of CAST whose focus is on computing, system theory, and technology that exploit the tolerance for imprecision and uncertainty to achieve tractability, robustness, and low cost. Soft computing is currently viewed as a junction of fuzzy logic, neural computing, probabilistic reasoning, and genetic algorithms. Soft system theory is based on fuzzy set theory, fuzzy measure theory, rough set theory, and their combinations. Soft technology plays a dual role in SCAST. Its first role is to develop supporting software and hardware for soft computing, while its second role is to develop applications of soft computing and soft systems theory in other areas. These various components of SCAST and their relationship are overviewed.
Preview
Unable to display preview. Download preview PDF.
References
Black, M., “Vagueness: an exercise in logical analysis.” Philosophy of Science, 4, 1937, pp. 427–455 (reprinted in Intern. J. of General Systems, 17 (2–3), 1990, pp. 107–128).
Choquet, G., “Theory of capacities.” Annales de L'Institut Fourier, 5, 1953–54, pp. 131–295.
Christensen, R., Entropy Minimax Sourcebook, Vol. IV: Applications. Entropy, Lincoln, MA, 1981.
Christensen, R., “Entropy minimax multivariate statistical modeling — I: Theory.” Intern. J. of General Systems, 11(3), 1985, pp. 231–277.
Christensen, R., “Entropy minimax multivariate statistical modeling — II: Applications.” Intern. J. of General Systems, 12(3), 1986, pp. 227–305.
Dubois, D. and H. Prade,Possibility Theory. Plenum Press, New York, 1988.
Dubois, D. and H. Prade, “Rough fuzzy sets and fuzzy rough sets.” Intern. J. of General Systems, 17(2–3), 1990, pp. 191–209.
Dubois, D. and H. Prade, “Putting rough sets and fuzzy sets together.” In: Slowinski, R., ed., Intelligent Decision Support. Kluwer, Boston, 1992, pp. 203–232.
Geer, J. F. and G. J. Klir, “A mathematical analysis of informationprocessing transformation between probabilistic and possibilistic formulations of uncertainty.” Intern. J. of General Systems, 20(2), 1992, pp. 143–176.
Gibbs, J. W., Elementary Principles in Statistical Mechanics. Yale University Press, New Haven (reprinted by Ox Bow Press, Woodbridge, Connecticut in 1981), 1902.
Goldberg, D. E.,Genetic Algorithms. Addison-Wesley, Reading, Mass., 1989.
Guan, J. W. and D. A. Bell,Evidence Theory and Its Applications, Vol. 1. North-Holland, New York, 1991.
Guan, J. W. and D. A. Bell,Evidence Theory and Its Applications, Vol. 2. North-Holland, New York, 1992.
Harmanec, D. and G. J. Klir, “Measuring total uncertainty in Dempster-Shafer theory: A novel approach.” Intern. J. of General Systems, 22(4), 1994, pp. 405–419.
Harmanec, D., G. J. Klir and G. Resconi, “On a modal logic interpretation of Dempster-Shafer theory of evidence.” Intern. J. of Intelligent Systems, (in production), 1994
Hartley, R. V. L., “Transmission of information.” The Bell Systems Technical journal, 7, 1928, pp. 535–563.
Hertz, J., A. Krogh and R. G. Palmer,Introduction to the Theory of Neural Computation. Addison-Wesley, Reading, Mass., 1991.
Holland, J.,Adaptation in Natural and Artificial Systems. Univ. of Michigan Press, Ann Arbor, 1975.
Klir, G. J., “A principle of uncertainty and information invariance.” Int. J. of General Systems, 17(2–3), 1990, pp. 249–275.
Klir, G. J., “Developments in uncertainty-based information.” In: Yovits, M. C., ed., Advances in Computers, Vol. 36. Academic Press, San Diego, 1993, pp. 255–332.
Klir, G. J., “Multivalued logics versus modal logics: Alternative frameworks for uncertainty modelling.” In: Wang, P. P., ed., Advances in Fuzzy Theory and Technology, Vol. 2. Bookwrights Press, Durham, NC, 1994
Klir, G. J. and T. Folger,Fuzzy Sets, Uncertainty, and Information. Prentice-Hall, Englewood Cliffs, NJ, 1988.
Klir, G. J. and D. Harmanec, “On modal logic interpretation of possibility theory.” Intern. J. of Uncertainty, Fuzziness, and Knowledge-Based Systems, 2(2), 1994
Klir, G. J. and B. Yuan,Fuzzy Sets and Fuzzy Logic: Theory and Applications. Prentice Hall, Englewood Cliffs, NJ, 1995.
Kruse, R. and K. D. Meyer,Statistics with Vague Data. D. Reidel, Boston, 1987.
Kuhn, T. S.,The Structure of Scientific Revolutions. Univ. of Chicago Press, Chicago, 1962.
Kyburg, H. E., “Bayesian and non-Bayesian evidential updating.” Artifical Intelligence, 31, 1987, pp. pp.271–293.
Moore, R. E.,Methods and Applications of Interval Analysis. SIAM, Philadelphia, 1979.
Pawlak, Z.,Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer, Boston, 1991.
Pichler, F. and R. Moreno Diaz, (eds.),Computer Aided Systems Theory — EUROCAST'93. Springer-Verlag, New-York, 1994.
Pichler, F. and H. Schwärtzel, (eds.),CAST Methods in Modeling. Springer-Verlag, New York, 1992.
Resconi, G., G. J. Klir and U. St. Clair,“Hierarchical uncertainty metatheory based upon modal logic.” Intern. J. of General Systems, 21(1), 1992, pp. 23–50.
Resconi, G., G. J. Klir, U. St. Clair and D. Harmanec,“On the integration of uncertainty theories.” Intern. J. of Uncertainty, Fuzziness, and Knowledge-Based Systems, 1(1), 1993, pp. 1–18.
Shafer, G., A Mathematical Theory of Evidence. Princeton Univ. Press, Princeton, N.J, 1976.
Simon, H. A.,The Sciences of the Artificial. M.I.T. Press, Cambridge, Mass., 1969.
Smithson, M.,Ignorance and Uncertainty: Emerging Paradigms. Springer-Verlag, New York, 1989.
Sugeno, M.,Theory of Fuzzy Integrals and its Applications. (Ph. D. dissertation). Tokyo Institute of Technology, Tokyo, 1974.
Sugeno, M.,“Fuzzy measures and fuzzy integrals: A survey.” In: Gupta, M. M., G. N. Saridis and B. R. Gaines, eds., Fuzzy Automata and Decision Processes. North-Holland, Amsterdam and New York, 1977, pp. 89–102.
Walley, P.,Statistical Reasoning With Imprecise Probabilities. Chapman and Hall, London, 1991.
Wang, Z. and G. J. Klir,Fuzzy Measure Theory. Plenum Press, New York, 1992.
Weaver, W., “Science and complexity.” American Scientist, 36, 1948, pp. 536–544.
Yager, R. R., S. Ovchinnikov, R. M. Tong and H. T. Nguyen, eds.,Fuzzy Sets and Applications — Selected Papers by L.A.Zadeh. John Wiley, New York, 1987.
Zadeh, L. A., “Fuzzy sets.” Information and Control, 8(3), 1965, pp. 338–353.
Zadeh, L. A., “Fuzzy sets as a basis for a theory of possibility.” Fuzzy Sets and Systems, 1(1), 1978, pp. 3–28.
Zadeh, L. A., “The birth and evolution of fuzzy logic.” Intern J. of General Systems, 17(2–3), 1990, pp. 95–105.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1996 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Klir, G.J. (1996). Soft Computer-Aided System Theory and Technology (SCAST). In: Klir, G.J., Ören, T.I. (eds) Computer Aided Systems Theory — CAST '94. Lecture Notes in Computer Science, vol 1105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61478-8_64
Download citation
DOI: https://doi.org/10.1007/3-540-61478-8_64
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-61478-4
Online ISBN: 978-3-540-68600-2
eBook Packages: Springer Book Archive