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Natural ventilation of animal houses clearly has advantages as for instance its low power consumption. However its application is often limited due to the lack of a reliable measuring and control system of the ventilation rate and so of emissions, as required for legislation.
Although a lot of models exist to determine natural ventilation rates in buildings, it is still a challenge to know the ventilation rate accurately with few measurements. The objective of this work was to develop a model for the prediction of the natural ventilation rate in a pig house with as few measuring points as possible. Neural networks were used to investigate the reliability and accuracy of using as limited input as possible, taken from data collected from measurements with sonic anemometers in a real scale test building under outside weather conditions.
Translated title of the contributionBepalen van debiet in natuurlijk geventileerde stallen door gebruik te maken van meettechnieken en neurale netwerken
Original languageEnglish
Title of host publicationInternational Conference of Agricultural Engineering - AgEng 2014 Zurich - Engineering for Improving Resource Efficiency
Number of pages8
PublisherThe European Society of Agricultural Engineers (EurAgEng)
Publication date7-Jul-2014
ISBN (Electronic)978-0-9930236-0-6
Publication statusPublished - 7-Jul-2014
EventAgEng 2014 - Zurich, Switzerland
Duration: 7-Jul-201410-Jul-2014

ID: 3057082