Prof. Manjeet Kumar* writes about Soft computing.
Prof. Kumar is a faculty in the area of IT at NIILM CMS. He can be contacted at manjeet@niilm.com
Soft
computing is the state-of-the-art approach to artificial intelligence, and it
mainly comprises fuzzy logic, neural networks and probabilistic reasoning. It
aims at mimic human reasoning particularly in computer milieu, and hence in
practice, the Soft computing systems are adaptive and intelligent in nature.
Soft
computing has also a user friendly Interface in the world of computing.
The
main constituents of soft computing are-
·
Fuzzy systems or
Impression
·
Neural Networks
or Learning
·
Probalostic
Reasoning or uncertainty
·
Evolutionary
Computing or optimization
Fuzzy Systems
A
fuzzy system is a system based on
fuzzy logic - a mathematical system that analyzes analog input values in terms
of logical variables that take on continuous values between 0 and 1, in
contrast to classical or digital logic, which operates on discrete values of
either 0 and 1 (true and false).
The
main Function of Fuzzy logic is to deal with Imprecision and Uncertainity.It
also deals with imprecise entities in automotive environments. It is based on
fuzzy sets and Fuzzy logic.
An Artificial Neural
Network (ANN) is an information processing paradigm that is inspired by the way
biological nervous systems, such as the brain, process information. The key
element of this paradigm is the novel structure of the information processing
system. An ANN is configured for a specific application, such as pattern
recognition or data classification, through a learning process.
Probabilistic
reasoning
In
a probalistic neural network (Bayesian learning) probality is used to represent
uncertainty about the relationship being learned. Before any data is seen the
prior opinion about what the true relationship might be can be expressed in a
probality distribution over the network weights that define this relationship.
Therefore
proballistic reasoning is done to make a solution of an uncertainty using a
Bayesian Network.
Evolutionary
Computing
Evolutionary computing is the field of
study devoted to the design, development, and analysis of problem solvers based
on natural selection. It is the field which is based on the study of techniques
used for problem solving like its development, design and analysis.
Advantages of
soft Computing
*
models
based human reasoning
*
models
can be
-
linguistic
-
simple
-
comprehensive
-
fast
when computing
-
good
practices
Soft Computing
Today
1.
Computing
with words(CW)
2.
Theory
of information granulation(TFIG)
3.
Computation
theory of perceptions(CTP)
Possible Soft
computing data and operations
1.
Numeric
data: 5, about 5, 5 to 6, about 5 to 6
2.
Linguist
data: Cheap, very big, not high, medium or bad.
3.
Functions
and relations: F(x), about f(x), fairly similar, much greater.
Conclusion
We
hereby conclude that the soft computing method is the only way to compute in
better and accurate way as it is more suitable than hard computing.
To know more about the soft computing, visit http://www.springer.com/series/2941
He is an M.Tech in IT and has a work experience of more than 8 years. He had worked in various fields like research, consultancy and academics.. He has several professional trainings in Information Technology. His research area includes Data Mining, Web Technology, ERP, Operating System, TQM. He Published 10 papers in National Conference/Seminar and 4 Papers in International Journal.
Great post. An excellent review of soft computing shared. It also has a user friendly Interface in the world of computing which is good. Thanks for sharing the soft computing review.
ReplyDeleteVery nice overview shared about soft computing. Components and advantages of soft computing. Really impressive overview. Thanks for sharing.
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