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...
| Main Authors: | , |
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| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2008.
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| Series: | Studies in Fuzziness and Soft Computing,
223 |
| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
Table of Contents:
- 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.
