Using fuzzy cognitive maps for data abstraction and synthesis in decision making

Karl Perusich, Michael McNeese

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The abstraction of data into more usable formats is an important consideration in complex information processing environments. To be effective data abstraction must preserve the original behavior of the system it is modeling, while at the same reducing the cognitive loading of the decision maker by reducing the volume of information he or she must process. Fuzzy cognitive maps can be used as a template for data abstraction. Because they represent the causal reasoning of the decision maker about a problem, they inherently incorporate how the decision makers use information. A heuristic is presented that preserves the input-output relationship of the map by preserving the cycles present in the map.

Original languageEnglish (US)
Title of host publicationAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
PublisherIEEE
Pages5-9
Number of pages5
Publication statusPublished - 1997
EventProceedings of the 1997 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'97 - Syracuse, NY, USA
Duration: Sep 21 1997Sep 24 1997

Other

OtherProceedings of the 1997 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'97
CitySyracuse, NY, USA
Period9/21/979/24/97

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Media Technology

Cite this

Perusich, K., & McNeese, M. (1997). Using fuzzy cognitive maps for data abstraction and synthesis in decision making. In Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS (pp. 5-9). IEEE.