Neuro-Fuzzy and Soft Computing

1. Neuro-Fuzzy and Soft Computing
By- Adarsh Gupta
19/PPS/001
M.tech (Power System)

2. What is covered in this class?
We will teach techniques useful in creating intelligent software systems that
can deal with the uncertainty and imprecision of real world problems
Some components of Intelligent systems are
human-like - they possess human-like expertise within a specific domain,
adaptable - they adapt themselves and learn to do better in a changing
environment, and
explanations - they explain how they make decisions or take actions

3. How will we teach the techniques?
We will present
multiple techniques from Soft Computing +,
when each technique is applicable
examples of industrial applications
“If the only tool you have is a hammer, then every problem looks like
a nail”
- anonymous

4. What is Soft Computing?
Soft Computing is a field that currently includes
• Fuzzy Logic
• Neural Networks
• Probabilistic Reasoning(Genetic Algorithms, BBN), and
• Other related methodologies
• Case-Based Reasoning
Soft Computing combines knowledge, techniques, and methodologies
from the sources above to create intelligent systems

5. Why is this important?
The information revolution going on is
allowing us to automate information
processing tasks which require
intelligence much like the industrial
revolution automated manufacturing
tasks
“Soft Computing” techniques have
already been applied successfully.
Farming
corn & cows
Service
content and code
Industrial
Revolution
Information
Revolution
Manufacturing
chairs & cars

6. “The essence of soft computing is that unlike the
traditional, hard computing, soft computing is aimed at an
accommodation with the pervasive imprecision of the
real world. Thus, the guiding principle of soft computing
is to exploit the tolerance for imprecision, uncertainty,
and partial truth to achieve tractability, robustness, low
solution cost, and better rapport with reality”
- Lotfi Zadeh
Soft Computing

7. Fuzzy Logic - Kai
Sets with fuzzy boundaries
A = Set of tall people
Heights
(cm)
170
1.0
Crisp set A
Membership
function
Heights
(cm)
170 180
.5
.9
Fuzzy set A
1.0
A = Set of tall people

8. Fuzzy set theory provides a systematic calculus to
deal with imprecise or incomplete information
Fuzzy if-then rules are used in fuzzy inference
systems
If <1> is tall and <1> is athletic then <1> is good
basketball player.
Fuzzy Set Theory - Kai
A B T-norm
X Y
w
A’ B’ C
Z

9. “The essence of soft computing is that unlike the traditional, hard
computing, soft computing is aimed at an accommodation with the
pervasive imprecision of the real world. Thus, the guiding principle of
soft computing is to exploit the tolerance for imprecision, uncertainty,
and partial truth to achieve tractability, robustness, low solution cost,
and better rapport with reality”
- Lotfi Zadeh
Neural Networks - Kai
Network architecture
Weights on the links
x1
x2
y1
y2

10. Genetic Algorithms
An optimization technique
10010110
01100010
10100100
10011001
01111101
. . .
. . .
. . .
. . .
10010110
01100010
10100100
10011101
01111001
. . .
. . .
. . .
. . .
Selection Crossover Mutation
Current
generation
Next
generation
Elitism

11. Other Techniques - Bill
Bayesian belief networks
represent and reason with probabilistic knowledge
Decision Trees
classification using tree structure
Least-squares estimator
statistical regression
Hybrid approaches
use multiple techniques

12. Soft Computing is a Hybrid Method
x1
x2
y1
y2
dog
dag
Knowledge
base
Animal?
dog
Neural
Character
Recognizer

13. How does SC Relate to Other Fields
What is AI?
“AI is the study of agents that exist in an environment and perceive
and act.” (S. Russell and P. Norvig)
“AI is the art of making computers do smart things.” (Waldrop)
“AI is a programming style, where programs operate on data according to
rules in order to accomplish goals.” (W. A. Taylor)
“AI is the activity of providing such machines as computers with the ability
to display behavior that would be regarded as intelligent if it were
observed in humans.” (R. McLoed)

14. How does SC Relate to Other Fields
What is an Expert System (ES)?
User
Knowledge
Engineer
Knowledge
Acquisition
KB
rules
facts
Questions
Responses
Inference
Engine

15. How does SC relate to other fields?
AI
Soft Computing
Machine
Learning
symbolic
manipulation
uncertainty and imprecision
automatic
improvement
with
experience
Cognitive
Psychology
Study of the mind
Statistics Probability
(not possibility)

16. Soft Computing Characteristics
• Human Expertise (if-then rules, cases, conventional
knowledge representations)
• Biologically inspired computing models (NN)
• New optimization techniques (GA, simulated annealing)
• Model-free learning (NN, CBR)
• Fault tolerance (deletion of neuron, rule, or case)
• Real-world applications (large scale with uncertainties)

17. THANK YOU
The End