Prediction of health of dairy cattle from breath samples using neural network with parametric model of dynamic response of array of semiconducting gas sensors
Jw. Gardner et al., Prediction of health of dairy cattle from breath samples using neural network with parametric model of dynamic response of array of semiconducting gas sensors, IEE P-SCI M, 146(2), 1999, pp. 102-106
Citations number
14
Categorie Soggetti
Eletrical & Eletronics Engineeing
Journal title
IEE PROCEEDINGS-SCIENCE MEASUREMENT AND TECHNOLOGY
The authors report on the use of a sampling device to collect the breath fr
om individual members of a herd of dairy cattle juring a two-week period. T
he response of an array of sis semiconducting oxide gas sensors to the brea
ths samples has been recorded and subsequently modelled by a time-dependent
, linear, second-order system. Four characteristics sensor parameters have
been estimated using a neural network;. and these parameters have been used
to train a predictive multilayer perceptron network. The results show that
either a static response parameter (based on the difference in the signal
from zero time) or a single time constant can be used to predict reasonably
well the health of the cow as judged against blood samples. In both cases,
the identification rate of unknown samples being about 76%. Further improv
ements may be possible through the use of network compensation of variation
?; in sample temperature and humidity.