APPLICATION OF FUZZY METRICS IN CLUSTERING PROBLEMS OF AGRICULTURAL CROP VARIETIES

被引：1

作者：

Stamenkovic, Andrijana ^{[1
]}

Milosavljevic, Natasa ^{[2
]}

Ralevic, Nebojsa M. ^{[3
]}

机构：

[1] Univ Novi Sad, Fac Tech Sci, Dept Power Elect & Telecommun Engn, Trg Dositeja Obradovica 6, Novi Sad 21000, Serbia

[2] Univ Belgrade, Fac Agr, Dept Math & Phys, Nemanjina 6, Belgrade 11080, Serbia

[3] Univ Novi Sad, Fac Tech Sci, Dept Fundamental Sci, Trg Dositeja Obradovica 6, Novi Sad 21000, Serbia

来源：

EKONOMIKA POLJOPRIVREDA-ECONOMICS OF AGRICULTURE | 2024年 / 71卷 / 01期

关键词：

agricultural crop varieties; fuzzy metrics; mathematical modeling; machine learning; clustering; variable environment method;

D O I：

10.59267/ekoPolj2401121S

中图分类号：

F3 [农业经济];

学科分类号：

0202 ; 020205 ; 1203 ;

摘要：

The problem of image -based detection of the variety of beans, using artificial intelligence, is currently dealt with by scientists of various profiles. The idea of this paper is to show the possibility of applying different types of distances, primarily those that are fuzzy metrics, in clustering models in order to improve existing models and obtain more accurate results. The paper presents the method of variable neighborhood search, which uses both standard and fuzzy t -metrics and dual fuzzy s -metrics characterized by appropriate parameters. By varying those parameters of the fuzzy metric as well as the parameters of the metaheuristic used, we have shown how it is possible to improve the clustering results. The obtained results were compared with existing ones from the literature. The criterion function used in clustering is a fuzzy metric, which is proven in the paper.

引用

页码：121 / 134

页数：14

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