К содержанию
РецензированоEN2023

HARVEST HORIZON: A ROBUST CROP AND YIELD PREDICTION MODEL FOR AGRICULTURAL SUSTAINABILITY

Sherya Kalyani (Student, Computer Science & Engineering, K. K. Wagh Institute of Engineering and Research, Nashik, India)

Международный журнал передовых научных исследований · 01-05 · 2023

Аннотация

Accurate prediction of crop yields plays a pivotal role in modern agriculture, enabling informed decision-making for resource allocation and food security planning. This study presents "Harvest Horizon," a comprehensive crop and yield prediction model designed to enhance agricultural sustainability. The model leverages a combination of historical crop data, satellite imagery, weather patterns, and machine learning algorithms to forecast crop yields with high precision. By harnessing the power of data-driven approaches, Harvest Horizon offers a proactive solution to address the challenges posed by fluctuating climatic conditions and evolving agricultural practices. This research contributes to the advancement of precision agriculture and offers a promising tool for optimizing resource utilization, mitigating risks, and fostering global food security.

Доказательный фрагмент

«Accurate prediction of crop yields plays a pivotal role in modern agriculture, enabling informed decision-making for resource allocation and food security planning.»

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Демо-превью

Accurate prediction of crop yields plays a pivotal role in modern agriculture, enabling informed decision-making for resource allocation and food security planning. Полный текст публикации CiteX не хранит — доступ к первоисточнику открывается по DOI согласно лицензии издателя и выбранному плану.

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Тип
Журнал
Страна
Узбекистан
Ключевые слова
Crop prediction, yield forecasting, agricultural sustainability
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