Name
Abstract | ||
|---|---|---|
In this paper, classifiers based on Multi-Layer Perceptrons and Support Vector Machines are used in order to classify seismic events that occurred in metropolitan France. The results are exploited in the software RAMSES to help the seismic analysts to conduct efficiently the revision of the weekly French seismic bulletin. With 96.5% of good classification, and less than 7% of the events emphasized for verification, RAMSES strikingly improves the speed of the revision. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1016/j.engappai.2006.05.008 | Eng. Appl. of AI |
Keywords | Field | DocType |
support vector machines,seismic event classification,metropolitan france,seismic analyst,neural networks,weekly french seismic bulletin,good classification,software ramses,seismic event,multi-layer perceptrons,neural network,support vector machine,multi layer perceptron | Data mining,Computer science,Support vector machine,Software,Artificial intelligence,Artificial neural network,Metropolitan France,Perceptron,Machine learning | Journal |
Volume | Issue | ISSN |
19 | 7 | Engineering Applications of Artificial Intelligence |
Citations | PageRank | References |
2 | 0.43 | 3 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Mercier | 1 | 2 | 0.77 |
| Pierre Gaillard | 2 | 79 | 10.89 |
| Michaël Aupetit | 3 | 261 | 25.59 |
| Carole Maillard | 4 | 2 | 0.43 |
| Robert Quach | 5 | 2 | 0.43 |
| Jean-Denis Muller | 6 | 3 | 1.82 |