Estimation of Food Security Risk Level Using Z-Number-Based Fuzzy System

Fuzzy logic systems based on If-Then rules are widely used for modelling of the systems characterizing imprecise and uncertain information. These systems are basically based on type-1 fuzzy sets and allow handling the uncertain and imprecise information to some degree in the developed models. Zadeh...

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Main Authors: Rahib H. Abiyev, Kaan Uyar, Umit Ilhan, Elbrus Imanov, Esmira Abiyeva
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Journal of Food Quality
Online Access:http://dx.doi.org/10.1155/2018/2760907
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author Rahib H. Abiyev
Kaan Uyar
Umit Ilhan
Elbrus Imanov
Esmira Abiyeva
author_facet Rahib H. Abiyev
Kaan Uyar
Umit Ilhan
Elbrus Imanov
Esmira Abiyeva
author_sort Rahib H. Abiyev
collection DOAJ
description Fuzzy logic systems based on If-Then rules are widely used for modelling of the systems characterizing imprecise and uncertain information. These systems are basically based on type-1 fuzzy sets and allow handling the uncertain and imprecise information to some degree in the developed models. Zadeh extended the concept of fuzzy sets and proposed Z-number characterized by two components, constraint and reliability parameters, which are an ordered pair of fuzzy numbers. Here, the first component is used to represent uncertain information, and the second component is used to evaluate the reliability or the confidence in truth. Z-number is an effective approach to solving uncertain problems. In this paper, Z-number-based fuzzy system is proposed for estimation of food security risk level. To construct fuzzy If-Then rules, the basic parameters cereal yield, cereal production, and economic growth affecting food security are selected, and the relationship between these input parameters and risk level are determined through If-Then fuzzy rules. The fuzzy interpolative reasoning is proposed for construction of inference mechanism of a Z-number-based fuzzy system. The designed system is tested using Turkey cereal data for assessing food security risk level and prediction periods of the food supply.
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institution Kabale University
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language English
publishDate 2018-01-01
publisher Wiley
record_format Article
series Journal of Food Quality
spelling doaj-art-92d231e5cc5d40b28cc145cb4c21a0c02025-08-20T03:37:23ZengWileyJournal of Food Quality0146-94281745-45572018-01-01201810.1155/2018/27609072760907Estimation of Food Security Risk Level Using Z-Number-Based Fuzzy SystemRahib H. Abiyev0Kaan Uyar1Umit Ilhan2Elbrus Imanov3Esmira Abiyeva4Department of Computer Engineering, Applied Artificial Intelligence Research Centre, Near East University, Northern Cyprus, Mersin-10, TurkeyDepartment of Computer Engineering, Applied Artificial Intelligence Research Centre, Near East University, Northern Cyprus, Mersin-10, TurkeyDepartment of Computer Engineering, Applied Artificial Intelligence Research Centre, Near East University, Northern Cyprus, Mersin-10, TurkeyDepartment of Computer Engineering, Applied Artificial Intelligence Research Centre, Near East University, Northern Cyprus, Mersin-10, TurkeyDepartment of Computer Engineering, Applied Artificial Intelligence Research Centre, Near East University, Northern Cyprus, Mersin-10, TurkeyFuzzy logic systems based on If-Then rules are widely used for modelling of the systems characterizing imprecise and uncertain information. These systems are basically based on type-1 fuzzy sets and allow handling the uncertain and imprecise information to some degree in the developed models. Zadeh extended the concept of fuzzy sets and proposed Z-number characterized by two components, constraint and reliability parameters, which are an ordered pair of fuzzy numbers. Here, the first component is used to represent uncertain information, and the second component is used to evaluate the reliability or the confidence in truth. Z-number is an effective approach to solving uncertain problems. In this paper, Z-number-based fuzzy system is proposed for estimation of food security risk level. To construct fuzzy If-Then rules, the basic parameters cereal yield, cereal production, and economic growth affecting food security are selected, and the relationship between these input parameters and risk level are determined through If-Then fuzzy rules. The fuzzy interpolative reasoning is proposed for construction of inference mechanism of a Z-number-based fuzzy system. The designed system is tested using Turkey cereal data for assessing food security risk level and prediction periods of the food supply.http://dx.doi.org/10.1155/2018/2760907
spellingShingle Rahib H. Abiyev
Kaan Uyar
Umit Ilhan
Elbrus Imanov
Esmira Abiyeva
Estimation of Food Security Risk Level Using Z-Number-Based Fuzzy System
Journal of Food Quality
title Estimation of Food Security Risk Level Using Z-Number-Based Fuzzy System
title_full Estimation of Food Security Risk Level Using Z-Number-Based Fuzzy System
title_fullStr Estimation of Food Security Risk Level Using Z-Number-Based Fuzzy System
title_full_unstemmed Estimation of Food Security Risk Level Using Z-Number-Based Fuzzy System
title_short Estimation of Food Security Risk Level Using Z-Number-Based Fuzzy System
title_sort estimation of food security risk level using z number based fuzzy system
url http://dx.doi.org/10.1155/2018/2760907
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