Development and analysis of fuzzy expert data for technological adjustment of a grain harvester header

Abstract

The paper considers the problems of developing and presenting fuzzy expert data on external factors and adjustable parameters of the harvester header. The object domain “Technological adjustment of the harvester header” was studied. On the basis of the data, obtained from four experts a linguistic description of the problem statements was given, linguistic variables were introduced, membership functions were developed, consistency characteristic properties were calculated. The base of fuzzy expert knowledge intended for the unit of obtaining and updating knowledge of the decision support intelligent system by an operator in the field conditions was created. In order to estimate quality of the fuzzy expert data and define the degree of its suitability for application in intelligent information system we used the algorithm which provides setting the quality criteria, availability of feedback with experts to update the data, makes it possible to choose the optimal number of terms of the membership functions. The possibility of taking into account the expert data hierarchy in the given algorithm made it possible to introduce experts ranging according to their qualification, for this purpose Fishburn numbers were used as weightihg factors.