Data-Based Model Approach to Predict Internal Air Temperature in a Mechanically-Ventilated Broiler House

Lak-yeong Choi; Yeonghyun Chae; Se-yeon Lee; Jinseon Park; Se-woon Hong

doi:10.5389/KSAE.2022.64.5.027

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2022 Vol.64, Issue 5 Preview Page Next Page

Data-Based Model Approach to Predict Internal Air Temperature in a Mechanically-Ventilated Broiler House 데이터 기반 모델에 의한 강제환기식 육계사 내 기온 변화 예측

2022. pp. 27-39

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Abstract

The smart farm is recognized as a solution for future farmers having positive effects on the sustainability of the poultry industry. Intelligent microclimate control can be a key technology for broiler production which is extremely vulnerable to abnormal indoor air temperatures. Furthermore, better control of indoor microclimate can be achieved by accurate prediction of indoor air temperature. This study developed predictive models for internal air temperature in a mechanically-ventilated broiler house based on the data measured during three rearing periods, which were different in seasonal climate and ventilation operation. Three machine learning models and a mechanistic model based on thermal energy balance were used for the prediction. The results indicated that the all models gave good predictions for 1-minute future air temperature showing the coefficient of determination greater than 0.99 and the root-mean-square-error smaller than 0.306℃. However, for 1-hour future air temperature, only the mechanistic model showed good accuracy with the coefficient of determination of 0.934 and the root-mean-square-error of 0.841℃. Since the mechanistic model was based on the mathematical descriptions of the heat transfer processes that occurred in the broiler house, it showed better prediction performances compared to the black-box machine learning models. Therefore, it was proven to be useful for intelligent microclimate control which would be developed in future studies.

Keywords

Genetic algorithm

machine learning

mechanistic model

smart farm

References

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Information

Publisher :The Korean Society of Agricultural Engineers
Publisher(Ko) :한국농공학회
Journal Title :Journal of Korean Society of Agricultural Engineers
Journal Title(Ko) :한국농공학회논문집
Volume : 64
No :5
Pages :27-39
Received Date : 2022-08-20
Revised Date : 2022-09-04
Accepted Date : 2022-09-04
DOI :https://doi.org/10.5389/KSAE.2022.64.5.027

Journal of Korean Society of Agricultural Engineers ISSN:1738-3692(Print) 2093-7709(Online) 한국농공학회논문집

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