Bagher Jamali (4 results)

Author
Refine with Advanced Search

Refine your search

  • Books (4)

to

Custom price range (£)

to

    • Language: English

      Published by LAP Lambert Academic Publishing, 2012

      3848411172 / 9783848411177

      • Softcover

      Seller: preigu, Osnabrück, Germanypreigu

      5-star seller
      Contact seller

      Condition: New

      £ 38.38

      £ 60.10 shipping 
      Ships from Germany to U.S.A.

      Quantity: 5 available

      Taschenbuch. Condition: Neu. Nonlinear identification using adaptive local linear neuro-fuzzy | Application of nonlinear identification in chemical industry and geoscience | Bagher Jamali (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783848411177 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

    • Language: English

      Published by LAP LAMBERT Academic Publishing, 2012

      3848411172 / 9783848411177

      • Softcover

      Seller: Mispah books, Redhill, SURRE, United KingdomMispah books

      4-star seller
      Contact seller

      Condition: Used - As new

      £ 101.00

      £ 25.00 shipping 
      Ships from United Kingdom to U.S.A.

      Quantity: 1 available

      Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

    • Language: English

      Published by LAP Lambert Academic Publishing, 2012

      3848411172 / 9783848411177

      • Softcover
      • Print on Demand

      Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

      5-star seller
      Contact seller

      Condition: New

      £ 45.05

      £ 26.19 shipping 
      Ships from Germany to U.S.A.

      Quantity: 2 available

      Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Neural networks and fuzzy logic have some common features such as distributed representation of knowledge, ability to handle data with uncertainty and imprecision etc. Fuzzy logic has tolerance for imprecision of data, while neural networks have tolerance for noisy data. A neural network s learning capability provides a good way to adjust expert s knowledge and it automatically generates additional fuzzy rules and membership functions to meet certain specifications. This reduces the design time and cost. On the other hand, the fuzzy logic approach enhances the generalization capability of a neural network by providing more reliable output when extrapolation is needed beyond the limits of the training data. To simplify the design and optimization of fuzzy models, process learning techniques derived from neural networks (so called neuro-fuzzy approaches) can be used.Different architectures of neuro-fuzzy systems have been discussed by a number of researchers. In this research, neuro-fuzzy system networks are deployed and used for the dynamic modeling of a nonlinear MIMO system (heat recovery steam generator (HRSG)) and a permeability prediction process.

    • Language: English

      Published by LAP LAMBERT Academic Publishing, 2012

      3848411172 / 9783848411177

      • Softcover
      • Print on Demand

      Seller: moluna, Greven, Germanymoluna

      5-star seller
      Contact seller

      Condition: New

      £ 36.85

      £ 42.06 shipping 
      Ships from Germany to U.S.A.

      Quantity: Over 20 available

      Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jamali BagherMr. Jamali is a graduate at the Petroleum University of Technology where he serves as Instructor in Control Lab and Commissioning of the Electronic Lab. He is an expert in process control, identification and artificial i.