SOFT COMPUTING IN ANALYTICS: HANDLING IMPRECISION AND UNCERTAINTY IN STRATEGIC DECISIONS
Additional contact information
Christer Carlsson: Institute for Advanced Management Systems Research, Abo Akademi University, 20520 Turku, Finland
Fuzzy Economic Review, 2012, vol. XVII, issue 2, 3-21
Analytics has a similar agenda as management science and is working with the same industrial and business context to support managerial planning, problem solving and decision making. Analytics has a broader scope in terms of methods – besides models and algorithms it also works with statistical methods and advanced technology for handling data, information and knowledge. Soft Computing builds on fuzzy sets theory, fuzzy logic, optimisation, neural nets, evolutionary algorithms, macro heuristics and approximate reasoning. Soft Computing is is focused on the design of intelligent systems to process uncertain, imprecise and incomplete information. Soft Computing methods applied to real-world problems offer more robust, tractable and less costly solutions than those obtained by more conventional mathematical techniques.
Keywords: analytics; management science; soft computing; fuzzy real options (search for similar items in EconPapers)
JEL-codes: C60 D81 (search for similar items in EconPapers)
References: Add references at CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:fzy:fuzeco:v:xvii:y:2012:i:2:p:3-21
Access Statistics for this article
More articles in Fuzzy Economic Review from International Association for Fuzzy-set Management and Economy (SIGEF) Contact information at EDIRC.
Bibliographic data for series maintained by Aurelio Fernandez (). This e-mail address is bad, please contact .