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A fuzzy expert system for business intelligence

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dc.contributor.author Mendis, D.S.K.
dc.contributor.author Karunananda, A.S.
dc.contributor.author Samaratunga, U.
dc.contributor.author Rathnayake, U.
dc.date.accessioned 2016-05-12T05:54:21Z
dc.date.available 2016-05-12T05:54:21Z
dc.date.issued 2013
dc.identifier.citation Mendis, D.S.K., Karunananda, A.S., Samaratunga, U. and Rathnayake, U. 2013. A fuzzy expert system for business intelligence. Proceedings of the 10th International Conference on Business Management. p. 24-31. en_US
dc.identifier.uri
dc.identifier.uri http://repository.kln.ac.lk/handle/123456789/13072
dc.description.abstract Business Intelligence (BI) is recognized as an increasingly important support for business decision making in emerging business environment, where a huge amount of data is growing fast and scattered around. Explicit knowledge can be presented formally and capable of effective (fast and good quality) communication of data to the user where as commonsense knowledge can be represented in informal way and further modeling needed for BI. Acquiring useful Business Intelligence (BI) for decision-making is a challenging task in dynamic business environment. In this paper we present an approach for modeling commonsense knowledge in Business Intelligence. A fuzzy expert system based on principal component analysis (PCA) and statistical fuzzy inference system for modeling Business Intelligence in commonsense knowledge is introduced in, which enables holistic approach for disaster management. This paper describes one such approach using classification of human constituents in Ayurvedic medicine. Evaluation of the system has shown 77% accuracy. en_US
dc.language.iso en en_US
dc.subject Business Intelligence en_US
dc.subject Statistical inference system en_US
dc.subject Common sense knowledge en_US
dc.subject Principal component analysis en_US
dc.subject Ayurvedic medicine en_US
dc.title A fuzzy expert system for business intelligence en_US
dc.type Article en_US


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