Name
Title | ||
|---|---|---|
Unsupervised Technique for Automatic Selection of Performance Indicators in Self-Organizing Networks. |
Abstract | ||
|---|---|---|
Self-organizing networks (SONs) aim at automating the management of cellular networks. However, tasks, such as the selection of the most appropriate performance indicators for SON functions, are still carried out by experts. In this letter, an unsupervised and autonomous technique for the selection of the most useful performance indicators is proposed, consisting in a data clustering stage followe... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/LCOMM.2017.2728012 | IEEE Communications Letters |
Keywords | Field | DocType |
Optimized production technology,Databases,Cellular networks,Artificial neural networks,Measurement,Neurons,Self-organizing networks | Data mining,Performance indicator,Feature selection,Computer science,Self-organizing network,Cellular network,Artificial intelligence,Artificial neural network,Cluster analysis,Machine learning | Journal |
Volume | Issue | ISSN |
21 | 10 | 1089-7798 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Palacios | 1 | 4 | 2.82 |
| Raquel Barco | 2 | 364 | 41.12 |