Eliciting Expert Knowledge for Fuzzy Evaluation of Agricultural Production Systems

Abstract

Public concern nowadays is an important frame of reference for the\\ndevelopment of agricultural production systems. The development of\\nsuch systems, therefore, involves both society level and production\\nsystem level. Following Zadeh\\'s principle of incompatibility,\\ninformation obtained at production system level is interpreted at\\nsociety level in linguistic terms. Fuzzy models promise to be a\\nvaluable tool as they link measurable information to linguistic\\ninterpretation using membership functions. The objective of this paper\\nis to outline a procedure which deals with criticism regarding the\\ninherent subjectivity in the construction of membership functions when\\nusing expert knowledge. The procedure guarantees the selection of\\nappropriate expert knowledge, and provides a guideline supporting the\\nselection of methods to elicit expert knowledge and construct\\nmembership functions. Also on the basis of the results in an\\nillustrative example, it is concluded that the procedure outlined in\\nthis paper suitably deals with criticism regarding membership\\nfunctions and, therefore, enables a practical implementation of fuzzy\\nevaluation of agricultural production systems. Current research\\nimplements the procedure to build a fuzzy model which evaluates egg\\nproduction systems in relation to public concern about the welfare of\\nlaying hens.