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Cluster analysis, fuzzy sets, and fuzzy logic models in bird identification

Осадчий, В. В. and Єремєєв, В. С. and Мацюра, О. В. (2017) Cluster analysis, fuzzy sets, and fuzzy logic models in bird identification. Ukrainian Journal of Ecology, 7 (2). pp. 96-103.

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In our resent research (Osadchiy at al., 2016) we considered the mathematical model for the identifying of bird species according to the results of inaccurate field measurements. We used the total length of the bird, the wingspan, the wingbeat frequency, and the flight as the input factors of the model. Testing the model on a hypothetical case of identifying some target species, like Rook, Common raven, Mallard, White Stork, and Lapwing revealed that this model can be used for bird species identification with definite limitations. However, in previous model we applied the recognition algorithm that was based on the classical sections of mathematical statistics. The limitations of those model are obvious - it does not take into account many characteristics and behavioral features of birds that cannot be represented in numerical form, like diurnal activity pattern and flocking behavior. In this case the possibility of using the traditional sections of mathematical statistics is quite limited. The present study is devoted to the development of a mathematical method for the identifying of the bird species that based on cluster analysis with fuzzy logic and fuzzy sets which extends the possibilities of the algorithm that was previously proposed in our research.

Item Type: Article
Subjects: G Географія, Антропологія, Рекреація > GF Екологія людини. Антропогеографія
L Освіта > L Освіта (Загальне)
L Освіта > LB Теорія і практика освіти
Q Наука > QA Математика > QA76 Комп'ютерне програмне забезпечення
Q Наука > QL Зоологія
Divisions: Факультет інформатики, математики та економіки > Кафедра інформатики і кібернетики
Depositing User: Кафедра інформатики і кібернетики
Date Deposited: 11 Feb 2019 12:50
Last Modified: 02 Oct 2019 05:51

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