Type-2 Fuzzy Logic: Theory and Applications

This book describes new methods for building intelligent systems using type-2 fuzzy logic and soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including type-1 fuzzy logic, neural networks, and genetic algorithms, which can be used to create powerful hybrid int...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Castillo, Oscar (Συγγραφέας), Melin, Patricia (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
Σειρά:Studies in Fuzziness and Soft Computing, 223
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 1 Introduction to Type-2 Fuzzy Logic
  • 2 Type-1 Fuzzy Logic
  • 3 Type-2 Fuzzy Logic
  • 4 A Method for Type-2 Fuzzy Inference in Control Applications
  • 5 Design of Intelligent Systems with Interval Type-2 Fuzzy Logic
  • 6 Method for Response Integration in Modular Neural Networks with Type-2 Fuzzy Logic
  • 7 Type-2 Fuzzy Logic for Improving Training Data and Response Integration in Modular Neural Networks for Image Recognition
  • 8 Fuzzy Inference Systems Type-1 and Type-2 for Digital Images Edge Detection
  • 9 Systematic Design of a Stable Type-2 Fuzzy Logic Controller
  • 10 Experimental Study of Intelligent Controllers Under Uncertainty Using Type-1 and Type-2 Fuzzy Logic
  • 11 Evolutionary Optimization of Interval Type-2 Membership Functions Using the Human Evolutionary Model
  • 12 Design of Fuzzy Inference Systems with the Interval Type-2 Fuzzy Logic Toolbox
  • 13 Intelligent Control of the Pendubot with Interval Type-2 Fuzzy Logic
  • 14 Automated Quality Control in Sound Speakers Manufacturing Using a Hybrid Neuro-fuzzy-Fractal Approach
  • 15 A New Approach for Plant Monitoring Using Type-2 Fuzzy Logic and Fractal Theory
  • 16 Intelligent Control of Autonomous Robotic Systems Using Interval Type-2 Fuzzy Logic and Genetic Algorithms
  • 17 Adaptive Noise Cancellation Using Type-2 Fuzzy Logic and Neural Networks.