easy and effective ....

2. Soft computing is a field of computer
science which makes use of inexact
solutions for problems which has no
known method to compute an exact
solution
It uses imprecision, uncertainty, partial
truth, and approximation as input

3. It’s aim is to exploit the tolerance for
Approximation, Uncertainty, Imprecision,
and Partial Truth in order to achieve close
resemblance with human like decision
making
The main goal of soft computing is to
develop intelligent machines to provide
solutions to real world problems, which are
not modeled, or too difficult to model
mathematically.

4. Soft = Evolutionary + Neural + Fuzzy
Computing Computing Network Logic
Zadeh Rechenberg McCulloch Zadeh
1981 1960 1943 1965
Evolutionary = Genetic + Evolution + Evolutionary + Genetic
Computing Programming Strategies programming Algorithms
Rechenberg Koza Rechenberg Fogel Holland
1960 1992 1965 1962 1970

5.  Hard computing
Deals with precise values
Accurate output is needed
Useful in critical systems
 Soft computing
 Deals with assumptions
Accuracy is not necessary
Useful for routine,control, decison making tasks

6. • Fuzzy Systems
•Neural Networks
•Evolutionary Computation
• Machine Learning
•Probabilistic Reasoning

7. • Founded in 1940
• Artificial neural network mimics the
biological neuron network in function
k

8. An NN, in general, is a highly interconnected
network of a large number of processing
elements called neurons in an architecture
inspired by the brain.
NN Characteristics are:-
Mapping Capabilities / Pattern Association
Generalisation
Robustness
Fault Tolerance
Parallel and High speed information processing

9. • Based on fuzzy set theory and fuzzy logic
• Uses numeric ranges of sets (fuzzy sets )
to measure and represent the logical
evaluations of partially accurate findings
• Most applications in control and decision
making
• Founded by Lofti A Zadeh

11. )

13.  Pattern recognition
based on training
data,Classification
supervised by
instructor.
 Unsupervised machine
learning is also used
where the machine
learns from the given
data by detecting
patterns.
Orange
Apple?
Instructor

14.  Models based on human reasoning.
 Closer to human thinking and biologically
inspired
 Models can be
 Linguistic
 Comprehensible
 Fast when computing
 Effective in practice.

15.  Heavy industry
 Robotic arms, Humanoid robots
 Home appliances
 Washing machines, ACs,
Refrigerators, cameras
 Automobiles
 Travel Speed Estimation, Sleep
Warning Systems, Driver-less
cars
 Spacecrafts
 Maneuvering of a Space
Shuttle(FL), Optimization of Fuel-
efficient Solutions for space craft

17. Soft Computing can be extended to include bio-
informatics aspects.
Fuzzy system can be applied to the construction
of more advanced intelligent industrial systems.
Soft computing is very effective when it’s applied
to real world problems that are not able to
solved by traditional hard computing.
Soft computing enables industrial to be
innovative due to the characteristics of soft
computing: tractability, low cost and high
machine intelligent quotient.