Development of a neural network mathematical model for demand forecasting in fluctuating markets

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dc.contributor.authorZiarati, Martin
dc.contributor.authorBilgili, Erdem
dc.contributor.authorSingh, Lakhvir
dc.contributor.authorAkdemir, Başak
dc.contributor.authorZiarati, Reza
dc.date.accessioned2015-09-22T16:03:47Z
dc.date.available2015-09-22T16:03:47Z
dc.date.issued2013-09-19
dc.description.abstractResearch has shown that Neural Networks (NNs) when trained appropriately are the best forecasting system compared to conventional techniques. Research has shown that there is no system to accurately forecast sudden changes in demand for a given product. This paper reports on the development of a recovery method when a sudden change in demand has taken place. This error in forecasting demand leads to either excessive inventories of the product or shortages of it and can lead to substantial financial losses for the company producing or marketing the product. Two recovery methods have been developed and described in this paper: RZ recovery and Exponential Smoothing (ES). In the RZ recovery once a sudden change has taken place, a ‘soft’ Poke-Yoke (PY) system is setup warning the company that the normal forecasting system can no longer be relied upon and a recovery system needs to be initiated, with re-forecasting initiated.en_UK
dc.identifier.citationZiarati M., Akdemir B., Bilgili E., Ziarati R. and Singh L. (2013). Development of a neural network mathematical model for demand forecasting in fluctuating markets. Proceedings of the 11th International Conference on Manufacturing Research (ICMR2013), Cranfield University, UK, 19th – 20th September 2013, pp 163-168en_UK
dc.identifier.isbn9781907413230
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/9456
dc.language.isoenen_UK
dc.publisherCranfield University Pressen_UK
dc.relation.ispartofseriesUncertainty and Modellingen_UK
dc.relation.ispartofseries9en_UK
dc.subjectforecastingen_UK
dc.subjectartificial neural networken_UK
dc.subjectexponential smoothingen_UK
dc.titleDevelopment of a neural network mathematical model for demand forecasting in fluctuating marketsen_UK
dc.typeConference proceedingsen_UK

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