NEURAL NETWORKS FOR THE SIMULATION OF MICROCLIMATIC PARAMETERS IN DAIRY HOUSES

Abstract

The aim of the present paper is to study natural ventilation in a dairy house by means of a parametric analysis relating wind speed and direction to the air flows through the ridge vent of the building. This analysis was carried out by means of an artificial neural network (ANN) which capability in modelling and simulating some climatic parameters inside a dairy house has been validated using the data collected in a trial carried out during summer 2005. The results show that modelling a Generalized feed-forward Multi-Layer Perceptron ANN allowed to obtain satisfactory results in the simulation of air speed and direction and air temperature and humidity inside a dairy house, using as input the values of wind speed and direction and outdoor air temperature and humidity. The adequate accuracy in the simulation of the air motion across the ridge vent allowed to perform a parametric analysis of the ventilation, which provided the values of air speed and direction in function of a fixed range of values of wind speed and direction.

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Published
2009-06-30
Section
Original Articles
Keywords:
natural ventilation, generalized multilayer perceptron, livestock building
Statistics
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PDF: 266
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How to Cite
D’Emilio, A., Mazzarella, R., & Porto, S. M. (2009). NEURAL NETWORKS FOR THE SIMULATION OF MICROCLIMATIC PARAMETERS IN DAIRY HOUSES. Journal of Agricultural Engineering, 40(2), 45-53. https://doi.org/10.4081/jae.2009.2.45