Data-Driven Optimization Method for Recurrent Neural Network Algorithm: Greenhouse Internal Temperature Prediction Model

Data-Driven Optimization Method for Recurrent Neural Network Algorithm: Greenhouse Internal Temperature Prediction Model

We developed an internal environment prediction model for smart greenhouses using machine learning models. Machine learning models were developed by finding certain rules based on the data obtained from the target system and have the advantage of learning various characteristics that are difficult t...

Full description

Saved in:
Bibliographic Details
Main Authors: Kwang Cheol Oh, Sunyong Park, Seok Jun Kim, La Hoon Cho, Chung Geon Lee, Dae Hyun Kim
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Agronomy
Subjects:
smart greenhouse
artificial intelligence model
machine learning
data characteristics
Online Access:https://www.mdpi.com/2073-4395/14/11/2545
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2073-4395/14/11/2545

Similar Items