Name
Title | ||
|---|---|---|
Machine-learning algorithms for predicting on-farm direct water and electricity consumption on pasture based dairy farms. |
Abstract | ||
|---|---|---|
•Four machine-learning models analysed for dairy farm electricity & water prediction.•A support vector machine algorithm predicted electricity consumption to within 12%.•A random forest algorithm predicted water consumption to within 38%.•Model accuracy improved with increasing dairy cow numbers. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.compag.2018.03.023 | Computers and Electronics in Agriculture |
Field | DocType | Volume |
Predictive power,Electricity,Support vector machine,Algorithm,Milking,Artificial intelligence,Engineering,Artificial neural network,Random forest,Decision tree learning,Machine learning,Linear regression | Journal | 150 |
ISSN | Citations | PageRank |
0168-1699 | 0 | 0.34 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| P. Shine | 1 | 0 | 0.68 |
| Michael D. Murphy | 2 | 4 | 2.28 |
| John Upton | 3 | 4 | 1.94 |
| Ted Scully | 4 | 17 | 4.25 |