Name
Abstract | ||
|---|---|---|
In the case of large-scale surveys, such as a Census, data may contain errors or missing values. An automatic error correction procedure is therefore needed. We focus on the problem of restoring the consistency of agricultural data concerning cultivation areas and number of livestock, and we propose here an approach to this balancing problem based on optimization. Possible alternative models, either linear, quadratic or mixed integer, are presented. The mixed integer linear one has been preferred and used for the treatment of possibly unbalanced data records. Results on real-world Agricultural Census data show the effectiveness of the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s11590-013-0652-3 | Optimization Letters |
Keywords | Field | DocType |
Data mining, Balancing problems, Information reconstruction, Mixed integer linear models | Integer,Mathematical optimization,Discrete optimization,Quadratic equation,Error detection and correction,Agriculture,Missing data,Census,Data records,Mathematics | Journal |
Volume | Issue | ISSN |
8 | 4 | 1862-4480 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gianpiero Bianchi | 1 | 3 | 1.40 |
| Renato Bruni | 2 | 127 | 15.79 |
| Alessandra Reale | 3 | 3 | 1.09 |