Content deleted Content added
m Reverted edits by 202.149.199.26 (talk) to last version by 140.180.240.254 |
MichaelMaggs (talk | contribs) Adding local short description: "Types of approximate algorithm", overriding Wikidata description "computing that is tolerant of imprecision, uncertainty, partial truth, and approximation" |
||
Line 1:
{{Short description|Types of approximate algorithm}}
'''Soft computing''' is an umbrella term used to describe types of [[algorithm]]s that produce approximate solutions to unsolvable high-level problems in computer science. Typically, traditional hard-computing algorithms heavily rely on concrete data and [[Mathematical Models and Methods in Applied Sciences|mathematical models]] to produce solutions to problems. Soft computing was coined in the late 20th century.<ref>{{Cite journal |last=Zadeh |first=Lotfi A. |date=March 1994 |title=Fuzzy logic, neural networks, and soft computing |journal=Communications of the ACM |language=en |volume=37 |issue=3 |pages=77–84 |doi=10.1145/175247.175255 |issn=0001-0782|doi-access=free }}</ref> During this period, revolutionary research in three fields greatly impacted soft computing. Fuzzy logic is a computational paradigm that entertains the uncertainties in data by using levels of truth rather than rigid 0s and 1s in binary. Next, neural networks which are computational models influenced by human brain functions. Finally, evolutionary computation is a term to describe groups of algorithm that mimic natural processes such as evolution and natural selection.
| |||