TY  - JOUR
AB  - 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.
VL  - 103
IS  - 9
SN  - 0263-5577
DO  - 10.1108/02635570310506133
UR  - https://doi.org/10.1108/02635570310506133
AU  - Nikolopoulos K.
AU  - Assimakopoulos V.
PY  - 2003
Y1  - 2003/01/01
TI  - Theta intelligent forecasting information system
T2  - Industrial Management & Data Systems
PB  - MCB UP Ltd
SP  - 711
EP  - 726
Y2  - 2024/04/19
ER  -