Soft computing

Soft computing is a set of algorithms,[1] including neural networks, fuzzy logic, and evolutionary 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.

Concept illustration of Soft computing

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
  • Soft Computing[5]
  • Applied Soft Computing[6]

References
  1. 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
  2. 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
  3. 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.
  4. 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.
  5. "Soft Computing". Springer. ISSN 1432-7643. Retrieved 2021-02-26.
  6. Applied Soft Computing. Elsevier B.V. ISSN 1568-4946.


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