Analysis of Formal Concepts for Verification of Pests and Diseases of Crops Using Machine Learning Methods

This article is devoted to a set of important areas of research: the analysis of formal representations and verification of pests and pathogens affecting crops using spectral brightness coefficients (SBR) for the period from 2021 to 2023. The database contains about 10,000 records covering the growi...

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Veröffentlicht in:	IEEE access Jg. 12; S. 19902 - 19910
Hauptverfasser:	Tussupov, Jamalbek, Yessenova, Moldir, Abdikerimova, Gulzira, Aimbetov, Aidyn, Baktybekov, Kazbek, Murzabekova, Gulden, Aitimova, Ulzada
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy metrics Artificial neural networks Brightness classification clustering Clustering algorithms Coordinates Crop production Crops Data analysis Data models data verification Disease control Diseases Earth Formal verification Machine learning Monitoring New technology Pests Remote sensing Satellite imagery Spectral analysis spectral brightness coefficient Vegetation mapping Verification
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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