Information Technology Reference
In-Depth Information
[2]
Arabshahi P, Choi JJ, Marks RJ, and Caudell TP (1992) Fuzzy control of
backpropagation. In: IEEE Internat. Conf. on Fuzzy Systems, San Diego: 967-972.
[3]
Bezdek JC (1992a) On the relationship between neural networks, pattern recognition
and intelligence. Int. J. Approximated Reasoning, 6: 85-102.
[4]
Bezdek JC (1992b) Computing with uncertainty. IEEE Commu. Magaz., Sept: 24-36.
[5]
Bloch I (1996) Information combination operators for data fusion: a comparative
review with classification. IEEE Trans. Syst. Man and Cybern. A26(1): 52-67.
[6]
Blum RI. (1982) Discovery and representation of causal relationship from a large
time-oriented clinical database: The RX project, Lecture Notes in Medical
Informatics, vol. 19:23-36, Springer-Verlag, New York.
[7]
Bonissone PP (1997) Soft computing: the convergence of merging reasoning
technologies. Soft Computing 1: 6-18.
[8]
Bonissone PP, Chen YT, Goebel K, and Khedkar PS (1999) Hybrid soft computing
systems: industrial and commercial applications. Proc. of the IEEE 87(9): 1641-1667.
[9]
Bosacci B (1997) On the role of soft computing in microelectronic industry. Soft
Computing 1: 57-60.
[10]
Dagli CH (ed.) (1994) Artificial neural networks in intelligent manufacturing.
Chapman and Hall, London.
[11]
Darwin C (1859) The origin of species. John Murray, London, UK.
[12]
Dubois D and Prade H (1993) Fuzzy sets and probability: misunderstandings, bridges
and gaps. Proc. of the Second IEEE Inter. Conf. On Fuzzy Systems, 2: 1059-1068.
[13]
Dubois D and Prade H (1998) Soft computing, fuzzy logic and artificial intelligence.
Soft Computing 2(1): 7-11.
[14]
Eberhard R, Simpson P, and Dobbins R (1995) Computational intelligence PC tools.
Academic Press, Boston, USA.
[15]
Emmanoulidis C, MacIntyre J, and Coxs C (1998) Neurofuzzy computing aided
machine fault diagnosis. Proc. of Joint Conf. on Information Sciences, 1:207-210.
[16]
Engelbrecht AP (2002) Computational intelligence: an introduction, Wiley, NJ.
[17]
Etzioni O (1996) The world-wide-web: Quagmire or goldmine? Communication,
ACM, 39:65-68.
[18]
Fogel DB (1995) Review of computational intelligence: imitating life (Zurada JM,
Marks RJ, and Robinson CJ, Eds.) IEEE Trans. on Neural Networks, 6(6): 1562-1565.
[19]
Fogel LLJ, Owens AJ, and Walsh (1966) Artificial intelligence through simulated
evolution. Wiley, New York.
[20]
Heider R (1996) Troubleshooting CFM 56-3 engines for the Boeing 737 using CBR
and data-mining. LNCS, vol. 1168:512-523, Springer-Verlag, New York.
[21]
Herrera F and Lozano M (1994) Adaptive genetic algorithm based on fuzzy
techniques. In: Proc. of IPMU '96, Granada, Spain: 775-780.
[22]
Holland JH (1975) Adaptation in natural and artificial Systems. The University of
Michigan Press, Ann Arbor, Michigan.
[23]
Jang JSR (1993) ANFIS: Adaptive-network-based-fuzzy-inference system. IEEE
Trans. Syst. Man Cybern. 23(3):665-685.
[24]
Jang J-SR, Sun C-T, and Mizutani E (1997) Neuro-fuzzy and soft computing. Prentice
Hall, Upper Saddle River, NJ.
[25]
Kim D and Kim Ch (1997) Forecasting time series with genetic fuzzy predictor
ensemble. IEEE Trans. on Fuzzy Systems, 5(4): 523-535.
[26]
Kosko B (1990) Fuzziness versus probability. Int. J. General Syst. 17(2/3): 211-240.
[27]
Koza JR (1992) Genetic programming. The MIT Press, Cambridge, MA.
[28]
Major JA and Riedinger DR (1992) EFD- A hybrid knowledge statistical -based
system for the detection of fraud. Internat. J. Intelligent System, 7:687-703.
[29]
Maniezzo V (1994) Genetic evolution of the topology and weight distribution of
neural networks. IEEE Trans. on Neural Networks 5(1): 39-53.
Search WWH ::




Custom Search