Machine Learning Approach to Predict Air Temperature and Relative Humidity inside Mechanically and Naturally Ventilated Duck Houses: Application of Recurrent Neural Network

Machine Learning Approach to Predict Air Temperature and Relative Humidity inside Mechanically and Naturally Ventilated Duck Houses: Application of Recurrent Neural Network

The duck industry ranks sixth as one of the fastest-growing major industries for livestock production in South Korea. However, there are few studies quantitatively predicting the internal thermal and moisture environment of duck houses. In this study, high-accuracy recurrent neural network (RNN) mod...

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Bibliographic Details
Main Authors: Sang-yeon Lee, In-bok Lee, Uk-hyeon Yeo, Jun-gyu Kim, Rack-woo Kim
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Agriculture
Subjects:
duck house
environmental monitoring
prediction of internal environments
machine learning
recurrent neural network
Online Access:https://www.mdpi.com/2077-0472/12/3/318

Internet

https://www.mdpi.com/2077-0472/12/3/318

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