Neuro-fuzzy systems

My slides for a presentation on Neuro-Fuzzy Systems in college...

1. Neuro -Fuzzy Systems (NFS) Presented by Sagar Ahire

2. Neuro -Fuzzy System = Neural Network + Fuzzy System

3. Fuzzy Logic A form of logic that deals with approximate reasoning Created to model human reasoning processes Uses variables with truth values between 0 and 1

4. Characteristics of Fuzzy Logic Everything is a matter of degree Knowledge is interpreted as a collection of fuzzy constraints on a collection of variables Inference is viewed as the process of propagation of these constraints Any logic system can be fuzzified

5. Neural Network Simplified Mathematical model of brain-like systems Functions like a massively parallel distributed computation network Is not programmed, but is trained

6. Neural Network Input Weights Output

7. Comparison Point Fuzzy Systems Neural Network Knowledge Source Human Experts Sample Sets Learning Mechanism Induction Adjusting Weights Reasoning Mechanism Heuristic Search Parallel Computation Learning Speed High Low Reasoning Speed Low High Fault Tolerance Low Very High Implementation Explicit Implicit Flexibility Low High

8. Neuro -Fuzzy Systems (NFS) Were created to solve the trade-off between: The mapping precision & automation of Neural Networks The interpretability of Fuzzy Systems Combines both such that either: Fuzzy system gives input to Neural Network Neural Network gives input to Fuzzy Systems

9. Steps in Development of NFS Development of Fuzzy Neural Models [Neurons] Development of synaptic connection models which incorporate fuzziness into Neural Network [Weights] Development of Learning Algorithms [Method of adjusting weights]

10. Types of NFS Type Weights Inputs Outputs Applications Type Crisp Crisp Crisp N/A Type 1 Crisp Fuzzy Crisp Classification Type 2 Crisp Fuzzy Fuzzy Fuzzy IF-THEN Type 3 Fuzzy Fuzzy Fuzzy Fuzzy IF-THEN Type 4 Fuzzy Crisp Fuzzy Fuzzy IF-THEN Type 5 Crisp Crisp Fuzzy Unrealistic Type 6 Fuzzy Crisp Crisp Unrealistic Type 7 Fuzzy Fuzzy Crisp Unrealistic

11. Models of NFS Model 1: Fuzzy System → Neural Network Model 2: Neural Network → Fuzzy Systems

12. Models of NFS #1: Fuzzy System → Neural Network

13. Models of NFS #2: Neural Network → Fuzzy System

14. Applications of NFS Measuring opacity/transparency of water in washing machine – Hitachi, Japan Improving the rating of convertible bonds – Nikko Securities, Japan Adjusting exposure in photocopy machines – Sanyo, Japan Electric fan that rotates towards the user – Sanyo, Japan