Information Technology Reference
In-Depth Information
[13]
Hodgson PD (1996) Microstructure modeling for property prediction and control, J. of
Materials Process Technology, 60: 27-33.
[14]
Jang JSR (1993) ANFIS: Adaptive Network Based Fuzzy Inference System, IEEE
Trans. on SMC., 23(3): 665-685
[15]
Jang JSR, Sun CT (1995) Neuro-fuzzy modelling and control, Proc. of IEEE, 83:
378-406.
[16]
Kim D, Kim C (1997) Forecasting time series with genetic fuzzy predictor ensemble,
IEEE Trans. on Fuzzy Systems, 5(4): 523-535.
[17]
Kosko B (1992) Neural networks and fuzzy systems, Prentice Hall, Englewood Cliffs,
New Jersey.
[18]
Kulkarni AD (1998) Neural-fuzzy models for multi-spectral image analysis, Internat.
J. of Applied Intelligence, 8: 173-187
[19]
Kulkarni AD (2001) Computer vision and fuzzy-neural systems, Upper Saddle River,
New Jersey: Prentice Hall PTR.
[20]
Lai JH and Lin CT (1999) Application of neural fuzzy network to pyrometer
correction and temperature control in rapid thermal processing, IEEE Trans. Fuzzy
Systems, 7(2):160-174.
[21]
Lee SH, Kim I (1994) Time series analysis using fuzzy learning, Proc. of Intern. Conf.
on Neural Information Processing, Seoul, Korea, 6: 1577-1582.
[22]
Li X, Dong S, Venuvinod PK (2000) Hybrid Learning for tool wear monitoring, Int. J.
Adv. Manufacturing Technology, 16: 303-307.
[23]
Lin CT and Lee CSG (1991) Neural networks based fuzzy logic and control systems,
IEEE Trans. On Computers, vol. 40, pp. 1320-1336.
[24]
M ATLAB (1998) Fuzzy logic toolbox, user's guide, The Math Works Inc., vers. 5.2
[25]
Mitra S, Hayashi Y (2000) Neuro-fuzzy rule generation: survey in soft computing
framework, IEEE Trans. on Neural Networks, 11(3): 748-768.
[26]
Nauck D, Klawonn F and Kruse R (1997) Foundations of neuro-fuzzy systems,
Wiley, Chichester, U.K.
[27]
Nie J (1997) Nonlinear time-series forecasting : A fuzzy-neural approach,
Neurocomputing, 16(1997): 63-76.
[28]
Pal SK and Mitra S (1992) Multilayer perceptron, fuzzy sets and classification, IEEE
Trans. On Neural Networks, 2(5): 683-697.
[29]
Palit AK and Babuška R (2001) Efficient training algorithm for Takagi-Sugeno type
neuro-fuzzy network, Proc. of FUZZ-IEEE, Melbourne, Australia, vol. 3: 1367-1371.
[30]
Palit AK and Popovic D (1999) Forecasting chaotic time series using neuro-fuzzy
approach, Proc. of IEEE-IJCNN, Washington DC, USA, vol. 3: 1538-1543.
[31]
Palit AK and Popovic D (1999) Fuzzy logic based automatic rule generation and
forecasting of time series, Proc. of FUZZ-IEEE, Seoul, Korea, vol. 1: 360-365.
[32]
Palit AK and Popovic D (2000) Intelligent processing of time series using neuro-
fuzzy adaptive genetic approach, Proc. of IEEE-ICIT, Goa, India, vol. 1:141-146.
[33]
Palit AK and Popovic D (2000) Nonlinear combination of forecasts using artificial
neural network, fuzzy logic and neuro-fuzzy Approaches, Proc. of FUZZ-IEEE, San
Antonio, Texas, USA, vol. 2: 566-571.
[34]
Palit AK, Doeding G, Anheier W, Popovic D (2002) Backpropagation based training
algorithm for Takagi-Sugeno type MIMO neuro-fuzzy network to forecast electrical
load time series, Proc. of FUZZ-IEEE, Honolulu, Hawai, USA. vol. 1: 86-91.
[35]
Park HS, Oh SK, Ahn TC and Pedrycz W (1999) A study on multi-layer based fuzzy
polynomial inference system based on an extended GMDH algorithm, Proc. of FUZZ-
IEEE, Seoul, Korea, vol. 1: 354-359
[36]
Pedrycz W (1995) Fuzzy sets engineering, CRC Press, Boca Raton, Florida.
[37]
Pickering FB (1978) Physical metallurgy and the design of steels, Applied Science,
London, U.K.
Search WWH ::




Custom Search