KJCKorea
Journal Central

@article{ART002726058},
author={Park GiCheol and SeongHun-Lee and Park Jaehwa},
title={Method for predicting the diagnosis of mastitis in cows using multivariate data and Recurrent Neural Network},
journal={Journal of Software Assessment and Valuation},
issn={2092-8114},
year={2021},
volume={17},
number={1},
pages={75-82},
doi={10.29056/jsav.2021.06.10}

TY - JOUR
AU - Park GiCheol
AU - SeongHun-Lee
AU - Park Jaehwa
TI - Method for predicting the diagnosis of mastitis in cows using multivariate data and Recurrent Neural Network
JO - Journal of Software Assessment and Valuation
PY - 2021
VL - 17
IS - 1
PB - Korea Software Assessment and Valuation Society
SP - 75
EP - 82
SN - 2092-8114
AB - Mastitis in cows is a major factor that hinders dairy productivity of farms, and many attempts have been made to solve it. However, research on mastitis has been limited to diagnosis rather than prediction, and even this is mostly using a single sensor. In this study, a predictive model was developed using multivariate data including biometric data and environmental data. The data used for the analysis were collected from robot milking machines and sensors installed in farmhouses in Chungcheongnam-do, South Korea. The recurrent neural network model using three weeks of data predicts whether or not mastitis is diagnosed the next day. As a result, mastitis was predicted with an accuracy of 82.9%. The superiority of the model was confirmed by comparing the performance of various data collection periods and various models
KW - Mastitis Prediction;Multivariate data;ICT;Smart Farm;Deep Learnin
DO - 10.29056/jsav.2021.06.10
ER -

Park GiCheol, SeongHun-Lee and Park Jaehwa. (2021). Method for predicting the diagnosis of mastitis in cows using multivariate data and Recurrent Neural Network. Journal of Software Assessment and Valuation, 17(1), 75-82.

Park GiCheol, SeongHun-Lee and Park Jaehwa. 2021, "Method for predicting the diagnosis of mastitis in cows using multivariate data and Recurrent Neural Network", Journal of Software Assessment and Valuation, vol.17, no.1 pp.75-82. Available from: doi:10.29056/jsav.2021.06.10

Park GiCheol, SeongHun-Lee, Park Jaehwa "Method for predicting the diagnosis of mastitis in cows using multivariate data and Recurrent Neural Network" Journal of Software Assessment and Valuation 17.1 pp.75-82 (2021) : 75.

Park GiCheol, SeongHun-Lee, Park Jaehwa. Method for predicting the diagnosis of mastitis in cows using multivariate data and Recurrent Neural Network. 2021; 17(1), 75-82. Available from: doi:10.29056/jsav.2021.06.10

Park GiCheol, SeongHun-Lee and Park Jaehwa. "Method for predicting the diagnosis of mastitis in cows using multivariate data and Recurrent Neural Network" Journal of Software Assessment and Valuation 17, no.1 (2021) : 75-82.doi: 10.29056/jsav.2021.06.10

Park GiCheol; SeongHun-Lee; Park Jaehwa. Method for predicting the diagnosis of mastitis in cows using multivariate data and Recurrent Neural Network. Journal of Software Assessment and Valuation, 17(1), 75-82. doi: 10.29056/jsav.2021.06.10

Park GiCheol; SeongHun-Lee; Park Jaehwa. Method for predicting the diagnosis of mastitis in cows using multivariate data and Recurrent Neural Network. Journal of Software Assessment and Valuation. 2021; 17(1) 75-82. doi: 10.29056/jsav.2021.06.10

Park GiCheol, SeongHun-Lee, Park Jaehwa. Method for predicting the diagnosis of mastitis in cows using multivariate data and Recurrent Neural Network. 2021; 17(1), 75-82. Available from: doi:10.29056/jsav.2021.06.10

Park GiCheol, SeongHun-Lee and Park Jaehwa. "Method for predicting the diagnosis of mastitis in cows using multivariate data and Recurrent Neural Network" Journal of Software Assessment and Valuation 17, no.1 (2021) : 75-82.doi: 10.29056/jsav.2021.06.10