Development of a control system using the fuzzy set theory applied to a browning process––towards a control system of the browning process combining a diagnosis model and a decision model––part II

2004 ◽  
Vol 64 (4) ◽  
pp. 507-514 ◽  
Author(s):  
I. Ioannou ◽  
N. Perrot ◽  
G. Mauris ◽  
G. Trystram
1981 ◽  
Vol 25 (1) ◽  
pp. 306-310
Author(s):  
Richard A. Newman

Fuzzy Set Theory has proved popular for development of decision making models. However, most such models have not been tested using problems such as commonly found in Human Factors system design. This study used a decision model that combined Fuzzy Set decision rules with an eigenvector weighting rule. Five experienced Human Factors Designers solved six design problems, half manually, and half using a computer program that served as a decision making aid, using the model. On completion of the procedure, the computer model made a recommendation for a solution. The user could accept or reject the model's choice. Comparisons were made between manual and computer aided decision making, and the Fuzzy Set decision rule was compared with other possible decision rules using the same data. Results showed that use of the model-based decision aid was accepted by the users, and were reasonable. In addition, a possible measure of decision making quality was found in the measure of weighting inconsistency which is part of the eigenvector procedure.


2020 ◽  
Vol 265 ◽  
pp. 121779 ◽  
Author(s):  
Luiz Maurício Furtado Maués ◽  
Brisa do Mar Oliveira do Nascimento ◽  
Weisheng Lu ◽  
Fan Xue

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