Information Technology Reference
In-Depth Information
[30]
Marks RJ (1993) Intelligence: computational versus artificial. (Editorial) Trans. on
Neural Networks, 4(5): 737-739.
[31]
Minsky ML and Papert S (1969) Perceptrons. MIT Press, Cambridge, MA.
[32]
Mitra S and Mitra P (2002) Data mining in soft computing framework: a survey. IEEE
Trans. on Neural Networks, 13(1): 3-14.
[33]
Pedrycz, Vasilakos, and Karnouskos (2003/2004) IEEE Trans. on Syst. Man and
Cybern., special issue on computational intelligence in telecommunication networks
and internet service. Pt.-I, 33 (3): 294-426; Pt.-II, 33(4): 429-501; Pt.-III, 34(1):1-96.
[34]
Poole D, Mackworth, and Goebel R (1998) Computational intelligence: a logical
approach. Oxford University Approach, New York.
[35]
Popovic D and Bhatkar VP (1990) Distributed computer control for industrial
automation. Marcel Dekker Inc., New York .
[36]
Popovic D and Bhatkar VP (1994) Methods and tools for applied artificial
intelligence. Marcel Dekker Inc., New York.
[37]
Popovic D. and Vlacic Lj (1999) Mechatronics in engineering design and product
development. Marcel Dekker Inc., New York.
[38]
Rechenberg I (1973) Evolutionsstrategie: Optimierung technischer Systeme nach
Prinzipien der biologischen Evolution. Fromman-Holzborg Verlag, Stuttgart.
[39]
Renders YM and Bersini H (1994) Hybridizing genetic algorithms with hill climbing
methods for global optimization: two possible ways. 1st IEEE-CEC: 312-317.
[40]
Renders YM and Flasse SP (1970) Hybrid methods using genetics algorithms for
global optimisation. IEEE Trans. Syst. Man Cyber., 26(2): 243-258).
[41]
Rosenblatt F (1962) Principles of aerodynamics: perceptrons and the theory of brain
mechanics. Spartan Books, Washington D.C.
[42]
Ruspini EH (1996) The semantics of Approximated reasoning. In: Fuzzy logic and
neural network handbook, Chen CH (Editor), McGraw-Hill, New York:5.1-5.28.
[43]
Schwefel H-P (1975) Evolutionsstrategie und numerische optimierung. PhD Thesis,
Technical University Berlin.
[44]
Taniguchi S and Dote Y (2001) Sensor fault detection for uninterruptible power
supply control systems using fast fuzzy network and immune network. Proc. of the
SMC 2001: 7-10.
[45]
Tettamanzi A and Tomassini M. (2001) Soft computing: integrating evolutionary,
neural, and fuzzy systems. Springer-Verlag, Berlin.
[46]
Tzafestas SG (1999) Soft computing in systems and control technology. World
Scientific Series in Robotics and Intelligent Systems, Vol. 18.
[47]
Wang LX (1992) Fuzzy systems are universal approximators. Proc. Intl. Conf. on
Fuzzy Systems, San Francisco, CA: 1163-1172.
[48]
Wenig J (2003) Autonomous mental development: A new frontier for computational
intelligence, IEEE Connections. Nov 2003: 8-13.
[49]
Werbos P (1974) Beyond regression: new tools for prediction and analysis in the
behavioural science. PhD Thesis, Harvard University, Cambridge, MA.
[50]
Zadeh LA (1965)Fuzzy sets. Information and Control, 8: 338-353.
[51]
Zadeh LA (1979) A theory of approximate reasoning. In: Hayes P, Michie D, and
Mikulich I, eds. : Machine Intelligence, Halstead Press, New York: 149-194.
[52]
Zadeh LA (1993) Fuzzy logic, neural networks, and soft computing. Proc. IEEE Int.
Workshop Neuro Fuzzy Control, Muroran, Japan: 1-3.
[53]
Zadeh LA (1994) Soft computing and fuzzy logic. IEEE Software, Nov.: 48-58.
[54]
Zadeh LA (1995) Probability theory and fuzzy logic are complementary rather than
competitive. Technometrics 37: 271-276.
[55]
Zadeh LA (1996) The role of soft computing: An introduction to fuzzy logic in the
conception, design, and development of intelligent systems. Proc. IEEE Int.
Workshop Soft Computing in Industry, Muroran, Japan: 136-137.
Search WWH ::




Custom Search