Neuro-Fuzzy Systems(NFS)
Presented by Sagar Ahire
Neuro-Fuzzy System=
Neural Network+
Fuzzy System
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
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
Neural Network
• Simplified Mathematical model of brain-like systems
• Functions like a massively parallel distributed computation network
• Is not programmed, but is trained
Neural Network• Input• Weights• Output
ComparisonPoint 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
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
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]
Types of NFSType Weights Inputs Outputs Applications
Type 0 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
Models of NFS
• Model 1: Fuzzy System → Neural Network• Model 2: Neural Network → Fuzzy Systems
Models of NFS #1:Fuzzy System → Neural Network
Models of NFS #2:Neural Network → Fuzzy System
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
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