Name
Title | ||
|---|---|---|
Machine learning to detect behavioural anomalies in dairy cows under subacute ruminal acidosis |
Abstract | ||
|---|---|---|
•Cows activity is modified under an episode of subacute ruminal acidosis.•Thanks to Machine Learning (ML) one can predict cow activity from one day to another.•Discrepancies between ML-predicted and observed activity can reveal abnormal behaviour.•KNNR seems the most efficient algorithm for detecting abnormal activity and disease. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.compag.2020.105233 | Computers and Electronics in Agriculture |
Keywords | DocType | Volume |
Cattle,Sickness behaviour,Metabolic disease,Data mining,Real-Time Locating System | Journal | 170 |
ISSN | Citations | PageRank |
0168-1699 | 1 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicolas Wagner | 1 | 1 | 0.34 |
| Antoine, V. | 2 | 2 | 1.04 |
| Marie-Madeleine Mialon | 3 | 1 | 0.34 |
| Romain Lardy | 4 | 1 | 0.34 |
| Mathieu Silberberg | 5 | 1 | 0.34 |
| Jonas Koko | 6 | 1 | 0.34 |
| Isabelle Veissier | 7 | 1 | 0.68 |