Crop yield prediction algorithm (CYPA) in precision agriculture based on IoT techniques and climate changes

Agriculture faces a significant challenge in predicting crop yields, a critical aspect of decision-making at international, regional, and local levels. Crop yield prediction utilizes soil, climatic, environmental, and crop traits extracted via decision support algorithms. This paper presents a novel...

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Veröffentlicht in:	Neural computing & applications Jg. 35; H. 23; S. 17281 - 17292
1. Verfasser:	Talaat, Fatma M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.08.2023 Springer Nature B.V
Schlagworte:	Active learning Agricultural production Agriculture Algorithms Artificial Intelligence Big Data Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Crop yield Data Mining and Knowledge Discovery Decision making Image Processing and Computer Vision Machine learning Meteorology Original Article Pests Probability and Statistics in Computer Science Precision agriculture Crop yield prediction Active learning IoT
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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