Export Behaviour Modeling Using EvoNF Approach

Simple item page
dc.creatorEdwards, Ron
dc.creatorAbraham, Ajith
dc.creatorPetrovic-Lazarevic, Sonja
dc.date2004-05-16
dc.date.accessioned2026-07-07T03:21:16Z
dc.date.available2026-07-07T03:21:16Z
dc.descriptionThe academic literature suggests that the extent of exporting by multinational corporation subsidiaries (MCS) depends on their product manufactured, resources, tax protection, customers and markets, involvement strategy, financial independence and suppliers' relationship with a multinational corporation (MNC). The aim of this paper is to model the complex export pattern behaviour using a Takagi-Sugeno fuzzy inference system in order to determine the actual volume of MCS export output (sales exported). The proposed fuzzy inference system is optimised by using neural network learning and evolutionary computation. Empirical results clearly show that the proposed approach could model the export behaviour reasonable well compared to a direct neural network approach.
dc.identifierhttps://arxiv.org/abs/cs/0405049
dc.identifierhttp://arxiv.org/abs/cs/0405049
dc.identifierThe International Conference on Computational Science 2003 (ICCS 2003), Springer Verlag, Lecture Notes in Computer Science Volume 2660, Sloot P.M.A. et al (Eds.), pp. 169-178, 2003
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/32130
dc.subjectArtificial Intelligence
dc.subjectI.2.0
dc.titleExport Behaviour Modeling Using EvoNF Approach
dc.typetext

Files

Collections

arXiv