Soft Computing

Presented By:ARVIND SAHU.15070144108.

Principle of soft computing. Soft computing. Goals of soft computing. Problem solving techniques. Hard computing v/s soft computing. Techniques in soft computing. Advantages of soft computing. Applications of soft computing.

Agenda

The guiding principle of soft computing is to exploit these tolerance to achieve:-

• Flexibility.• Robustness.• Low Solution Cost.

Principle

Soft computing is the fusion of methodologies designed to model and enable solutions to real world problems, which are not modeled or too difficult to model mathematically.

The aim of soft computing is to exploit the tolerance for imprecision(not-repeatable), uncertainty, approximate reasoning, and partial truth in order to achieve close resemblance with human like decision making.

Soft Computing

Field of computer science which makes use of inexact solutions for problems which has no known method to compute an exact solution.

Problems in whose solutions are unpredictable, uncertain and between 0 and 1.

Fuzzy Logic, Neuro-Computing, Evolutionary and Genetic Computing, and Probabilistic Computing.

Soft Computing

Soft Evolutionary Neural Fuzzy

Computing Computing Network Logic

Soft Computing

SC = EC + NN + FL

To develop intelligent machines to provide solutions to real world problems, which are not modeled, or too difficult to model mathematically.

Well suited for real world problems where ideal solutions are not there.

Goals of Soft Computing

PROBLEM SOLVING TECHNIQUES

Hard computingDeals with precise values.Accurate output is needed.Useful in critical systems.

Soft computingDeals with assumptions.Accuracy is not necessary.Useful for routine, control, decision making

tasks.

Hard computing Vs. Soft computing

I. Fuzzy Systems. II. Neural Networks. III. Evolutionary Computation. IV. Machine Learning. V. Probabilistic Reasoning.

Techniques in Soft Computing

Machine Learning 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

Models based on human reasoning. Closer to human thinking and biologically

inspired. Models can be

i. Linguistic.ii. Fast when computing.iii. Effective in practice.

Advantages of SC

Heavy industry:- Robotic arms, Humanoid robots

Home appliances:- Washing machines, ACs, Refrigerators,

cameras

Automobiles:- Travel Speed Estimation, Sleep Warning

Systems, Driver-less cars

Application of soft computing

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