Temperature and Relative Humidity Prediction in Swine Livestock Buildings

Andres Molano-Jimenez; Alvaro D. Orjuela-Canon; Wilmer Acosta-Burbano

doi:10.1109/LA-CCI.2018.8625245

Temperature and Relative Humidity Prediction in Swine Livestock Buildings

Andres Molano-Jimenez, Alvaro D. Orjuela-Canon, Wilmer Acosta-Burbano

Producción científica: Contribución a una conferencia › Actas de congreso › revisión exhaustiva

2 Citas (Scopus)

Resumen

Based on available data from a swine livestock warehouse located in Puerto Gaitan - Meta, four models were proposed to predict relative humidity and temperature using artificial neural networks and measurements from temperature, humidity and CO₂ concentration. Results seem to indicate that the model structures used are suitable for predict humidity in barns not equipped with humidity sensors and improve current installed microclimate control systems in Colombia.

Idioma original	Inglés estadounidense
DOI	https://doi.org/10.1109/LA-CCI.2018.8625245
Estado	Publicada - ene. 23 2019
Publicado de forma externa	Sí
Evento	2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018 - Gudalajara, México Duración: nov. 6 2018 → nov. 9 2018

Conferencia

Conferencia	2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018
País/Territorio	México
Ciudad	Gudalajara
Período	11/6/18 → 11/9/18

Áreas temáticas de ASJC Scopus

Inteligencia artificial
Redes de ordenadores y comunicaciones
Gestión y sistemas de información

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

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10.1109/LA-CCI.2018.8625245

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Temperature and Relative Humidity Prediction in Swine Livestock Buildings. / Molano-Jimenez, Andres; Orjuela-Canon, Alvaro D.; Acosta-Burbano, Wilmer.
2019. Papel presentado en 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018, Gudalajara, México.

Producción científica: Contribución a una conferencia › Actas de congreso › revisión exhaustiva

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