Evolution and Neural Network Prediction of CO Emissions in Weaned Piglet Farms.
Journal:
Sensors (Basel, Switzerland)
Published Date:
Apr 11, 2022
Abstract
This paper aims to study the evolution of CO concentrations and emissions on a conventional farm with weaned piglets between 6.9 and 17.0 kg live weight based on setpoint temperature, outdoor temperature, and ventilation flow. The experimental trial was conducted during one transition cycle. Generally, the ventilation flow increased with the reduction in setpoint temperature throughout the cycle, which caused a reduction in CO concentration and an increase in emissions. The mean CO concentration was 3.12 g m. Emissions of CO had a mean value of 2.21 mg s per animal, which is equivalent to 0.195 mg s kg. A potential function was used to describe the interaction between 10 min values of ventilation flow and CO concentrations, whereas a linear function was used to describe the interaction between 10 min values of ventilation flow and CO emissions, with values of 0.82 and 0.85, respectively. Using such equations allowed for simple and direct quantification of emissions. Furthermore, two prediction models for CO emissions were developed using two neural networks (for 10 min and 60 min predictions), which reached values of 0.63 and 0.56. These results are limited mainly by the size of the training period, as well as by the differences between the behavior of the series in the training stage and the testing stage.