| 000 | 01884naa a22003378i 4500 | ||
|---|---|---|---|
| 999 |
_c5310 _d5310 |
||
| 001 | 00005310 | ||
| 003 | FR-PaOEC | ||
| 005 | 20211006062616.0 | ||
| 006 | a o d i | ||
| 007 | cr || |||m|n|| | ||
| 008 | 190601s2017 ||| o i|0| 0 eng d | ||
| 035 | _a(FR-PaOEC) | ||
| 040 |
_aFR-PaOEC _cES-MaONT |
||
| 100 | 1 |
_aOtani, Tomoyuki _93312 |
|
| 245 | 1 | 0 |
_aApplication of AI to mobile network operation / _cTomoyuki Otani ... [el al.] |
| 260 |
_aGeneva : _bInternational Telecommunication Union, _c2017. |
||
| 300 | _a7 p. | ||
| 336 |
_atexto (visual) _2isbdcontent |
||
| 337 |
_aelectrónico _2isbdmedia |
||
| 338 |
_arecurso en línea _2rdacarrier |
||
| 520 | 3 | _aWith the introduction of network virtualization and the implementation of 5G/IoT, mobile networks will offer more diversified services and be more complex. This raises a concern about a significant rise in network operation workload. Meanwhile, artificial intelligence (AI) technology is making remarkable progress and is expected to solve human resource shortages in various fields. Likewise, the mobile industry is gaining momentum toward the application of AI to network operation to improve the efficiency of mobile network operation [1][2].This paper will discuss the possibility of applying AI technology to network operation and presents some use cases to show good prospects for AI-driven network operation. | |
| 650 | 0 |
_aTecnologías habilitadoras digitales _918 |
|
| 653 | 4 | _aScience and Technology | |
| 700 | 1 |
_aToube, Hideki _93313 |
|
| 700 | 1 |
_aKimura, Tatsuya _93314 |
|
| 700 | 1 |
_aFurutani, Masanori _93315 |
|
| 773 | 0 |
_04843 _tITU Journal: ICT Discoveries _gVol. 2018, no. 1, p. 59-65 _q2018:1<59 _x2616-8375 |
|
| 856 | 4 | 0 |
_aitu-ilibrary.org _uhttps://www.itu.int/dms_pub/itu-s/opb/journal/S-JOURNAL-ICTS.V1I1-2017-7-PDF-E.pdf _yAcceso al documento _x0 _qpdf |
| 942 |
_cART _2udc |
||