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 had developed during his dissertation. In TIFIS, besides the traditional components of a decision‐support onformation 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.
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1 December 2003
Research Article|
December 01 2003
Theta intelligent forecasting information system Available to Purchase
K. Nikolopoulos;
K. Nikolopoulos
Forecasting Systems Unit, School of Electrical & Computer Engineering, National Technical University of Athens, Athens, Greece
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V. Assimakopoulos
V. Assimakopoulos
Forecasting Systems Unit, School of Electrical & Computer Engineering, National Technical University of Athens, Athens, Greece
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Publisher: Emerald Publishing
Online ISSN: 1758-5783
Print ISSN: 0263-5577
© MCB UP Limited
2003
Industrial Management & Data Systems (2003) 103 (9): 711–726.
Citation
Nikolopoulos K, Assimakopoulos V (2003), "Theta intelligent forecasting information system". Industrial Management & Data Systems, Vol. 103 No. 9 pp. 711–726, doi: https://doi.org/10.1108/02635570310506133
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