Soft Computing and Machine Learning

1. The difference between Soft Computing and Hard Computing and basics of Soft computing is explained in this lecture.

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 Soft Computing vs Hard Computing:-

 1. Soft Computing is tolerant of imprecision, uncertainty, partial truth, and approximation whereas  Hard Computing requires a precisely state analytic model.

2. Soft Computing is based on fuzzy logic, neural sets, and probabilistic reasoning whereas Hard Computing is based on binary logic, crisp system, numerical analysis, and crisp software.

3. Soft computing has the characteristics of approximation and dispositional whereas Hard computing has the characteristics of precision and categoricity.

4.  Soft computing can evolve its own programs whereas Hard computing requires programs to be written.

5. Soft computing can use multivalued or fuzzy logic whereas Hard computing uses two-valued logic.

6. Soft computing incorporates stochasticity whereas Hard computing is deterministic.

7.  Soft computing can deal with ambiguous and noisy data whereas Hard computing requires exact input data.

8. Soft computing allows parallel computations whereas Hard computing is strictly sequential.

9. Soft computing can yield approximate answers whereas Hard computing produces precise answers.

Difference between Soft Computing and Hard Computing

Soft Computing could be a computing model evolved to resolve the non-linear issues that involve unsure, imprecise, and approximate solutions of a tangle. These sorts of issues square measure thought of as real-life issues wherever the human-like intelligence is needed to resolve it.

Hard Computing is that the ancient approach employed in computing that desires Associate in Nursing accurately declared analytical model. the outcome of hard computing approach is a warranted, settled, correct result and defines definite management actions employing a mathematical model or algorithmic rule. It deals with binary and crisp logic that need the precise input file consecutive. Hard computing isn’t capable of finding the real world problem’s solution.