Review of Machine Learning Model Applications in Precision Agriculture
نویسندگان
چکیده
منابع مشابه
Application of Gis and Gps in Precision Agriculture (a Review)
Agriculture is a complex system science and the knowledge of it is consisting of much concepts and relationships. Examinations in connection with site-specific farming have been carried out by our institute since 1998. Precision farming is a way of agricultural production, which takes into account the in-field variability, a technology where the application-seeding, nutrient replacement, sprayi...
متن کاملApplication of GIS and GPS in Precision Agriculture (A Review)
Agriculture is a complex system science and the knowledge of it is consisting of much concepts and relationships. Examinations in connection with site-specific farming have been carried out by our institute since 1998. Precision farming is a way of agricultural production, which takes into account the in-field variability, a technology where the application-seeding, nutrient replacement, sprayi...
متن کاملApplication of Gis and Gps in Precision Agriculture (a Review)
Agriculture is a complex system science and the knowledge of it is consisting of much concepts and relationships. Examinations in connection with site-specific farming have been carried out by our institute since 1998. Precision farming is a way of agricultural production, which takes into account the in-field variability, a technology where the application-seeding, nutrient replacement, sprayi...
متن کاملApplication of GIS and GPS in Precision Agriculture (A Review)
Agriculture is a complex system science and the knowledge of it is consisting of much concepts and relationships. Examinations in connection with site-specific farming have been carried out by our institute since 1998. Precision farming is a way of agricultural production, which takes into account the in-field variability, a technology where the application-seeding, nutrient replacement, sprayi...
متن کاملMachine Learning Model Interpretability for Precision Medicine
Interpretability of machine learning models is critical for data-driven precision medicine efforts. However, highly predictive models are generally complex and are difficult to interpret. Here using Model-Agnostic Explanations algorithm, we show that complex models such as random forest can be made interpretable. Using MIMIC-II dataset, we successfully predicted ICU mortality with 80% balanced ...
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ژورنال
عنوان ژورنال: Advances in computer science research
سال: 2023
ISSN: ['2352-538X']
DOI: https://doi.org/10.2991/978-94-6463-136-4_81