Theta intelligent forecasting information system

Nikolopoulos, K; Assimakopoulos, V

dc.contributor.author	Nikolopoulos, K	en
dc.contributor.author	Assimakopoulos, V	en
dc.date.accessioned	2014-03-01T01:19:39Z
dc.date.available	2014-03-01T01:19:39Z
dc.date.issued	2003	en
dc.identifier.issn	0263-5577	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/15634
dc.subject	Forecasting	en
dc.subject	Information systems	en
dc.subject	Management	en
dc.subject	Modelling	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Engineering, Industrial	en
dc.subject.other	Decision making	en
dc.subject.other	Decision support systems	en
dc.subject.other	Inference engines	en
dc.subject.other	Intelligent agents	en
dc.subject.other	Object oriented programming	en
dc.subject.other	Technological forecasting	en
dc.subject.other	Decision support information system	en
dc.subject.other	Theta intelligent forecasting information system	en
dc.subject.other	Knowledge representation	en
dc.title	Theta intelligent forecasting information system	en
heal.type	journalArticle	en
heal.identifier.primary	10.1108/02635570310506133	en
heal.identifier.secondary	http://dx.doi.org/10.1108/02635570310506133	en
heal.language	English	en
heal.publicationDate	2003	en
heal.abstract	The need effectively to integrate decision making tasks together with knowledge representation and inference procedures has caused recent research efforts towards the integration of decision support systems with knowledge-based techniques. Explores the potential benefits of such integration in the area of business forecasting. Describes the forecasting process and identifies its main functional elements. Some of these elements provide the requirements for an intelligent forecasting support system. Describes the architecture and the implementation of such a system, the theta intelligent forecasting information system (TIFIS) that that first-named author has developed during his dissertation. In TIFIS, besides the traditional components of a decision-support information system, four constituents are included that try to model the expertise required. The information system adopts an object-oriented approach to forecasting and exploits the forecasting engine of the theta model integrated with automated rule based adjustments and judgmental adjustments. Tests the forecasting accuracy of the information system on the M3-competition monthly data.	en
heal.publisher	EMERALD GROUP PUBLISHING LIMITED	en
heal.journalName	Industrial Management and Data Systems	en
dc.identifier.doi	10.1108/02635570310506133	en
dc.identifier.isi	ISI:000225664700017	en
dc.identifier.volume	103	en
dc.identifier.issue	8-9	en
dc.identifier.spage	711	en
dc.identifier.epage	726	en