1. 1
Introduction to Neuro-fuzzy
and Soft computing
Dr. Prafull Chandra Narooka
Department of Computer Science
School of Engineering & Systems
Sciences
MDS University, Ajmer
2. What is computing?
2
Counting, calculating
The discipline of computing is the systematic study
of algorithmic processes that describe and transform
information: their theory, analysis, design, efficiency,
implementation, and application.
Types of computing
Hard computing
Soft Computing
3. Differences between hard and soft computing
3
Hard Computing Soft computing
Precisely stated analytical model Tolerant to imprecision,
uncertainty, partial truth,
approximation
Based on binary logic, crisp
systems, numerical analysis, crisp
software
Fuzzy logic, neural nets,
probabilistic reasoning.
Programs are to be written Evolve their own programs
Two values logic Multi valued logic
Exact input data Ambiguous and noisy data
Strictly sequential Parallel computations
Precise answers Approximate answers
4. Essence of SC:-
Accommodation
with the pervasive
imprecision of the
real world
Principle of SC:-
Exploit uncertainty
to achieve
robustness and
better rapport with
reality
4
5. Artificial intelligence
5
If intelligence can be induced in machines it is called
as artificial intelligence.
Soft computing is a part of artificial intelligent
techniques
Closed related to machine
intelligence/computational intelligence
6. What is Soft computing
6
Neural Networks
Fuzzy Inference
systems
Neuro-
Fuzzy
Computing
Derivative-
Free
Optimization
Soft Computing
+ =
7. What is Soft computing
7
Artificial Neural
Networks
Evolutionary
computation
Fuzzy logic
Heuristics
Soft
Computing
8. Introduction
8
SC is an innovative approach to
constructing computationally intelligent
systems
Intelligent systems that possess humanlike
expertise within a specific domain, adapt
themselves and learn to perform better in
changing environments
These systems explain how they make
decisions or take actions
They are composed of two features:
“adaptivity” & “knowledge
9. Introduction Contd….
9
Neural Networks (NN) that recognize patterns &
adapts themselves to cope with changing
environments
Fuzzy inference systems that incorporate human
knowledge & perform inference & decision making
Adaptivity + Expertise = NF & SC
10. What is the difference between Fuzzy Logic and Neural Networks?
10
Fuzzy logic allows making definite decisions based on
imprecise or ambiguous data
ANN tries to incorporate human thinking process to solve
problems without mathematically modeling them.
Both these methods can be used to solve nonlinear
problems, and problems that are not properly specified, but
they are not related.
ANN tries to apply the thinking process in the human brain
to solve problems.
11. Latest developments in the field of soft
computing
11
Areas of image processing
Image retrieval
Image analysis
Remote sensing
Data mining
Swarm intelligence
Diffusion process
Agent’s technology