DocumentCode :
3192465
Title :
Analytic Hierarchy Process and granularity: Assessment of risk severity on livestock wellness
Author :
Mohan, K.K. ; Reformat, Marek Z. ; Pedrycz, Witold
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Alberta, Edmonton, AB, Canada
fYear :
2012
fDate :
6-8 Aug. 2012
Firstpage :
1
Lastpage :
6
Abstract :
This paper presents a methodology for assessing risk severity based on an Analytic Hierarchy Process (AHP) model perceived as a structure with multiple levels of granularity. The quantification of risk severity is performed using two types of synthesis: top-down and bottom-up. The former one determines risk severity levels experienced by the overall objective due to all risk factors and sub-factors, whereas the latter approach determines severity levels due to individual, selected risk factors and sub-factors. Importantly, this paper attempts to bridge the hierarchical problem solving process using AHP methodology with granular computing in a pragmatic manner. This has been illustrated with an example of constructing a quantitative model for identifying risk factors in the outbreak of cattle diseases.
Keywords :
decision making; farming; granular computing; AHP model; analytic hierarchy process; bottom-up synthesis; cattle diseases; granular computing; granularity; livestock wellness; risk factor; risk severity assessment; top-down synthesis; Agriculture; Analytical models; Computational modeling; Cows; Diseases; Vectors; analytic hierarchy process (AHP); granularity; livestock; risk severity; weigh vector;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Information Processing Society (NAFIPS), 2012 Annual Meeting of the North American
Conference_Location :
Berkeley, CA
ISSN :
pending
Print_ISBN :
978-1-4673-2336-9
Electronic_ISBN :
pending
Type :
conf
DOI :
10.1109/NAFIPS.2012.6291021
Filename :
6291021
Link To Document :
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