Food Security Risk Level Assessment: a Fuzzy Logic-Based Approach

نویسندگان

  • Muhd Khairulzaman Abdul Kadir
  • Evor L. Hines
  • Kefaya Qaddoum
  • Rosemary Collier
  • Elizabeth Dowler
  • Wyn Grant
  • Mark S. Leeson
  • Daciana Iliescu
  • Arjunan Subramanian
  • Keith Richards
  • Yasmin Merali
  • Richard Napier
چکیده

A fuzzy logic (FL) based food security risk level assessment system is design in this paper. Three inputs – yield, production and economic growth, were 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 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 which may either assess current food security risk or predict periods or regions of impending pressure on food supply.

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عنوان ژورنال:
  • Applied Artificial Intelligence

دوره 27  شماره 

صفحات  -

تاریخ انتشار 2013