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Food security risk level assessment : a fuzzy logic-based approach

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Abdul Kadir, Muhd K., Hines, Evor, Qaddoum, Kefaya, Collier, Rosemary, Dowler, Elizabeth, Grant, Wyn, Leeson, Mark S., Iliescu, Daciana, Subramanian, Arjunan, Richards, Keith, Merali, Yasmin and Napier, R. (2013) Food security risk level assessment : a fuzzy logic-based approach. Applied Artificial Intelligence, Volume 27 (Number 1). pp. 50-61. doi:10.1080/08839514.2013.747372 ISSN 0883-9514.

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Official URL: http://dx.doi.org/10.1080/08839514.2013.747372

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Abstract

A fuzzy logic (FL)-based food security risk level assessment system is designed and is presented in this article. Three inputs—yield, production, and economic growth—are used to predict the level of risk associated with food supply. A number of previous studies have related food supply with risk assessment for particular types of food, but none of the work was specifically concerned with how the wider food chain might be affected. The system we describe here uses the Mamdani method. The resulting system can assess risk level against three grades: severe, acceptable, and good. The method is tested with UK (United Kingdom) cereal data for the period from 1988 to 2008. The approach is discussed on the basis that it could be used as a starting point in developing tools that may either assess current food security risk or predict periods or regions of impending pressure on food supply.

Item Type: Journal Article
Subjects: H Social Sciences > HD Industries. Land use. Labor
Divisions: Faculty of Science, Engineering and Medicine > Engineering > Engineering
Faculty of Social Sciences > Warwick Business School > Information Systems & Management
Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- )
Faculty of Social Sciences > Politics and International Studies
Faculty of Social Sciences > Sociology
Library of Congress Subject Headings (LCSH): Food security, Food supply -- Risk assessment, Fuzzy logic
Journal or Publication Title: Applied Artificial Intelligence
Publisher: Taylor & Francis Inc.
ISSN: 0883-9514
Official Date: 10 January 2013
Dates:
DateEvent
10 January 2013Published
Volume: Volume 27
Number: Number 1
Page Range: pp. 50-61
DOI: 10.1080/08839514.2013.747372
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 25 December 2015
Date of first compliant Open Access: 25 December 2015
Funder: Seventh Framework Programme (European Commission) (FP7), Great Britain. Department for Environment, Food and Rural Affairs (DEFRA), University of Warwick. School of Engineering, Malaysia, University of Malaya in Kuala Lumpur
Grant number: 211457 (FP7)

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