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Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

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advanced neuro fuzzy controller design
artificial neural networks
asynchronous transfer mode networks
Atm Network
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evolutionary computation methods
expert system applications
Fault Degree
Fault Diagnosis
Fuzzy Controllers
Fuzzy Logic
Fuzzy Logic Controller
Fuzzy Neural Controller
Fuzzy Neuro Controller
Fuzzy Rules
Fuzzy Sets
Fuzzy Systems
GA
genetic algorithms
industrial automation solutions
Input Phase Voltages
intelligent control systems
Knowledge Based Information Systems
knowledge-based information paradigms
Membership Function
Multiobjective Evolutionary Algorithms
Neural Net
NFS
Nonlinear Membership Functions
Output Line Voltages
Roulette Wheel Selection Scheme
speech recognition technology
Thrust Specific Fuel Consumption
Voltage Space Vectors
VRP

Product details

  • ISBN 9780849398049
  • Weight: 662g
  • Dimensions: 156 x 234mm
  • Publication Date: 17 Nov 1998
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Description

Artificial neural networks can mimic the biological information-processing mechanism in - a very limited sense. Fuzzy logic provides a basis for representing uncertain and imprecise knowledge and forms a basis for human reasoning. Neural networks display genuine promise in solving problems, but a definitive theoretical basis does not yet exist for their design.
Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms integrates neural net, fuzzy system, and evolutionary computing in system design that enables its readers to handle complexity - offsetting the demerits of one paradigm by the merits of another.
This book presents specific projects where fusion techniques have been applied. The chapters start with the design of a new fuzzy-neural controller. Remaining chapters discuss the application of expert systems, neural networks, fuzzy control, and evolutionary computing techniques in modern engineering systems. These specific applications include:

  • direct frequency converters
  • electro-hydraulic systems
  • motor control
  • toaster control
  • speech recognition
  • vehicle routing
  • fault diagnosis
  • Asynchronous Transfer Mode (ATM) communications networks
  • telephones for hard-of-hearing people
  • control of gas turbine aero-engines
  • telecommunications systems design
    Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms covers the spectrum of applications - comprehensively demonstrating the advantages of fusion techniques in industrial applications.
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    About
    Jain, Lakhmi C.; Martin, N.M.