Difference between revisions 535174544 and 539384750 on enwiki

{{Expert-subject|computer science|date=July 2009}}
{{Distinguish|soft microprocessor}}

'''Soft computing''' is a term applied to a field within computer science which is characterized by the use of inexact solutions to computationally hard tasks such as the solution of [[NP-complete]] problems, for which there is no known algorithm that can compute an exact solution in [[polynomial time]]. Soft computing differs from conventional (hard) computing in that, unlike hard computing(contracted; show full)arising in [[biology]], [[medicine]], the [[humanities]], [[management science]]s, and similar fields often remained intractable to conventional mathematical and analytical methods.  That said, it should be pointed out that simplicity and complexity of systems are relative, and many conventional mathematical models have been both challenging and very productive.
Soft computing deals with imprecision, uncertainty, partial truth, and approximation to achieve practicability, robustness and low solution cost.

there is a main difference between soft computing and possibility.possibility is used when we don't have enough information to solve a problem but soft computing is used when we don't have enough information about the problem itself.these kind of problems originate in human mind with all it's doubts,subjectivity and emotions like determining a suitable temperature for a room to make people feel comfortable.⏎
Components of soft computing include:
* [[Neural network]]s (NN)
* [[Fuzzy logic]]s (FL)
* [[Evolutionary computation]] (EC), including:
** [[Evolutionary algorithm]]s
*** [[Genetic algorithm]]s
*** [[Differential evolution]]
** [[Metaheuristic]] and [[Swarm Intelligence]]
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