Name
Abstract | ||
|---|---|---|
The detection of transients in the practice of continuous casting within a steel-making industry is a key task for the prediction of final product properties but currently a direct observation of this phenomenon is not available. For this reason in this paper several standard and soft-computing based methods for the detection of transients from plant data will be tested and compared. From the obtained results it emerges that the use of a fuzzy inference system based on experts knowledge achieves very satisfactory results correctly identifying most of the transient events present in the databases provided by different companies. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-21501-8_32 | IWANN (1) |
Keywords | Field | DocType |
final product property,different company,plant data,continuous casting,direct observation,steel casting,ai-based technique,fuzzy inference system,key task,steel-making industry,experts knowledge,satisfactory result | Data mining,Steel casting,Final product,Computer science,Artificial intelligence,Continuous casting,Machine learning,Fuzzy inference system | Conference |
Volume | ISSN | Citations |
6691 | 0302-9743 | 1 |
PageRank | References | Authors |
0.41 | 5 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Valentina Colla | 1 | 159 | 29.50 |
| Marco Vannucci | 2 | 94 | 15.60 |
| Nicola Matarese | 3 | 18 | 4.12 |
| Gerard Stephens | 4 | 1 | 0.41 |
| Marco Pianezzola | 5 | 1 | 0.41 |
| Izaskun Alonso | 6 | 1 | 0.41 |
| Torsten Lamp | 7 | 1 | 0.41 |
| Juan Palacios | 8 | 1 | 0.41 |
| Siegfried Schiewe | 9 | 1 | 0.41 |