Prediction of Internal Temperature in Greenhouses Using the Supervised Learning Techniques: Linear and Support Vector Regressions

Prediction of Internal Temperature in Greenhouses Using the Supervised Learning Techniques: Linear and Support Vector Regressions

Agricultural greenhouses must accurately predict environmental factors to ensure optimal crop growth and energy management efficiency. However, the existing predictors have limitations when dealing with dynamic, non-linear, and massive temporal data. This study proposes four supervised learning tech...

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Bibliographic Details
Main Authors: Fabián García-Vázquez, Jesús R. Ponce-González, Héctor A. Guerrero-Osuna, Rocío Carrasco-Navarro, Luis F. Luque-Vega, Marcela E. Mata-Romero, Ma. del Rosario Martínez-Blanco, Celina Lizeth Castañeda-Miranda, Germán Díaz-Flórez
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Applied Sciences
Subjects:
smart agriculture
data science
supervised learning
Online Access:https://www.mdpi.com/2076-3417/13/14/8531

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