Centroids Beyond Defuzzification

被引:0
|
作者
Figueroa Garcia, Juan Carlos [1 ]
Servin, Christian [2 ]
Kreinovich, Vladik [3 ]
机构
[1] Univ Dist Francisco Jose de Caldas, Bogota, Colombia
[2] El Paso Community Coll EPCC, Comp Sci & Informat Technol Syst Dept, 919 Hunter Dr, El Paso, TX 79915 USA
[3] Univ Texas El Paso, 500 W Univ, El Paso, TX 79968 USA
来源
基金
美国国家科学基金会;
关键词
D O I
10.1007/978-3-030-81561-5_35
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In general, expert rules expressed by imprecise (fuzzy) words of natural language like "small" lead to imprecise (fuzzy) control recommendations. If we want to design an automatic controller, we need, based on these fuzzy recommendations, to generate a single control value. A procedure for such generation is known as defuzzification. The most widely used defuzzification procedure is centroid defuzzification, in which, as the desired control value, we use one of the coordinates of the center of mass ("centroid") of an appropriate 2-D set. A natural question is: what is the meaning of the second coordinate of this center of mass? In this paper, we show that this second coordinate describes the overall measure of fuzziness of the resulting recommendation.
引用
收藏
页码:407 / 412
页数:6
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