Name
Abstract | ||
|---|---|---|
The connection of physical agriculture with corresponding cyber systems is helpful to achieve precision agriculture. Real-time data from agriculture sensors can provide decision supports to improve the yields and quality of agricultural products, but also bring about challenges one of which is how to mine useful information from these vast amounts of data at acceptable computation costs. To deal w... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TII.2019.2914158 | IEEE Transactions on Industrial Informatics |
Keywords | Field | DocType |
Support vector machines,Cyber-physical systems,Genetic algorithms,Soil,Big Data,Agriculture,Humidity | Computer science,Support vector machine,Real-time computing,Cyber-physical system,Agriculture,Artificial intelligence,Big data,Machine learning | Journal |
Volume | Issue | ISSN |
15 | 12 | 1551-3203 |
Citations | PageRank | References |
3 | 0.40 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junhu Ruan | 1 | 3 | 0.74 |
| Hua Jiang | 2 | 14 | 5.42 |
| Xiaoyu Li | 3 | 3 | 1.07 |
| Yan Shi | 4 | 285 | 27.64 |
| Felix T. S. Chan | 5 | 1267 | 113.20 |
| Weizhen Rao | 6 | 3 | 1.07 |