Difference between revisions 542374120 and 542629038 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)
Soft computing deals with imprecision, uncertainty, partial truth, and approximation to achieve practicability, robustness and low solution cost. As such it forms the basis of a considerable amount of [[machine learning]] techniques.


tThere is a main difference between soft computing and possibility.p 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.t These kind of problems originate in human mind with all it's doubts,  subjectivity and emotions;  an example can be determining a suitable temperature for a room to make people feel comfortable.<br />
Components of soft computing include:
* [[Neural network]]s (NN)
* [[Support Vector Machine]]s (SVM)
* [[Fuzzy logic]]s (FL)
* [[Evolutionary computation]] (EC), including:
** [[Evolutionary algorithm]]s
*** [[Genetic algorithm]]s
(contracted; show full)[[Category:Scientific modeling]]
[[Category:Artificial intelligence]]
[[Category:Semantic Web]]
[[Category:Soft computing]]
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