Soft computing
Soft computing is a set of algorithms,[1] including neural networks, fuzzy logic, and genetic algorithms.[2] These algorithms are tolerant of imprecision, uncertainty, partial truth and approximation. It is contrasted with hard computing: algorithms which find provably correct and optimal solutions to problems.
History
The theory and techniques related to soft computing were first introduced in 1980s.[3] The term "soft computing" was coined by Lotfi A. Zadeh.[4][1]
See also
Notable journals
References
- ^ a b Choudhury, Balamati; Jha, Rakesh Mohan, eds. (2016), "Soft Computing Techniques", Soft Computing in Electromagnetics: Methods and Applications, Cambridge: Cambridge University Press, pp. 9–44, doi:10.1017/CBO9781316402924.003, ISBN 978-1-107-12248-2, retrieved 2021-02-24
- ^ Shukla, K. K. (2000-01-01), Sinha, NARESH K.; Gupta, MADAN M. (eds.), "CHAPTER 17 - Soft Computing Paradigms for Artificial Vision", Soft Computing and Intelligent Systems, Academic Press Series in Engineering, San Diego: Academic Press, pp. 405–417, ISBN 978-0-12-646490-0, retrieved 2021-02-24
- ^ Ibrahim, Dogan (2016-01-01). "An Overview of Soft Computing". Procedia Computer Science. 12th International Conference on Application of Fuzzy Systems and Soft Computing, ICAFS 2016, 29–30 August 2016, Vienna, Austria. 102: 34–38. doi:10.1016/j.procs.2016.09.366. ISSN 1877-0509.
- ^ Zadeh, Lotfi A. (1994-03-01). "Fuzzy logic, neural networks, and soft computing". Communications of the ACM. 37 (3): 77–84. doi:10.1145/175247.175255. ISSN 0001-0782. S2CID 1824401.
- ^ "Soft Computing". Springer. ISSN 1432-7643. Retrieved 2021-02-26.
{{cite web}}: CS1 maint: url-status (link) - ^ Applied Soft Computing. Elsevier B.V. ISSN 1568-4946.
 | This artificial intelligence-related article is a stub. You can help Wikipedia by expanding it. |