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Neuro-fuzzy and soft computing: a computational
Neuro-fuzzy and soft computing: a computational

Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence by Chuen-Tsai Sun, Eiji Mizutani, Jyh-Shing Roger Jang

Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence



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Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence Chuen-Tsai Sun, Eiji Mizutani, Jyh-Shing Roger Jang ebook
Publisher: Prentice Hall
Page: 640
ISBN: 0132610663, 9780132610667
Format: djvu


(ed.) 2000 M.Dekker Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence Jang J.-S.R., Sun C.-T., Mizutani E. [1] Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, Jyh-Shing Roger Jang, Chuen-Tsai Sun, Eiji Mizutani. Computational Methods in Surface and Colloid Science Borowko M. JYH-SHING ROGER JANG, CHUEN-TSAI SUN & EIJI MIZUTANI (1997); Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, Prentice Hall Publishers.JOHN R. Some recent publications also demonstrate the increasing popularity of computational intelligence and machine learning concepts like ensemble methods, local learning and meta-learning in soft sensors. Hand DJ: Discrimination and classification. However, the proper selection of these Because of the advantages of the artificial intelligence systems, many researchers studied to find the relationships between input and output parameters in EDM process by using soft computing techniques. Jang JSR, Sun CT, Mizutani E: Neuro-fuzzy and soft computing: a Computational approach to learning and machine intelligence. The achievement of EDM process is affected by many input parameters; therefore, the computational relations between the output responses and controllable input parameters must be known. Upper Saddle River NJ: Prenctice Hall; 1997. Currently, a shift from traditional statistical PCA- / PLS-based techniques to more advanced approaches, like Artificial Neural Networks, kernel-based methods, Gaussian processes, Neuro-Fuzzy Systems can currently be observed in the field of soft sensor development. Neuro-Fuzzy and Soft Computing A Computational Approach to Learning and Machine Intelligence - Jyh-Shing Roger Jang Simulating Continuous Fuzzy Systems - James J.

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