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Bayesian and Graph Theory Approaches to Develop Strategic Early Warning Systems for the Milk Market

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Bayesian and Graph Theory Approaches to Develop Strategic Early Warning Systems for the Milk Market.pdf (240.8Kb)
Date
2015
Author
Gürpınar, Furkan
Bisson, Christophe
Diner, Öznur Yaşar
Abstract
This paper presents frameworks for developing a Strategic Early Warning System allowing the estimatation of the future state of the milk market. Thus this research is in line with the recent call from the EU commission for tools which help to better address such a highly volatile market. We applied different multivariate time series regression and Bayesian networks on a pre-determined map of relations between macro economic indicators. The evaluation of our findings with root mean square error (RMSE) performance score enhances the robustness of the prediction model constructed. Finally we construct a graph to represent the major factors that effect the milk industry and their relationships. We use graph theoretical analysis to give several network measures for this social network
 
such as centrality and density.
 

Source

New Contributions in Information Systems And Technologies, Vol 1, Pt 1

Volume

353

Pages

533-542

URI

https://hdl.handle.net/20.500.12469/625
https://dx.doi.org/10.1007/978-3-319-16486-1_52

Collections

  • Araştırma Çıktıları / Scopus [1565]
  • Araştırma Çıktıları / WOS [1518]
  • Enformasyon Teknolojileri [4]

Keywords

Strategic Early Warning System
Bayesian networks
Graph theory
Forecasting
Milk

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