Overview of Soft Computing

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.

What is a Neural Network?

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.