Optimizing Prediction Time and Accuracy of Users' Regular/Irregular Grouping Using ML Classification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00379519" target="_blank" >RIV/68407700:21230/24:00379519 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/VTC2024-Fall63153.2024.10757811" target="_blank" >https://doi.org/10.1109/VTC2024-Fall63153.2024.10757811</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/VTC2024-Fall63153.2024.10757811" target="_blank" >10.1109/VTC2024-Fall63153.2024.10757811</a>
Alternative languages
Result language
angličtina
Original language name
Optimizing Prediction Time and Accuracy of Users' Regular/Irregular Grouping Using ML Classification
Original language description
Utilization of Artificial Intelligence in mobile networks has seen significant growth in the last decade. It spans from mobile phone applications to various aspects of mobile network operations, including planning and optimization. Understanding and modeling users' mobility patterns enhance mobility-based operations such as handover, scheduling, paging, and caching. In the literature, numerous models exist for grouping users' mobility patterns in mobile networks based on their regularity. In our paper, we employ machine learning techniques to achieve this task, prioritizing low prediction time and high accuracy.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
100th IEEE Vehicular Technology Conference, VTC 2024-Fall
ISBN
9798331517786
ISSN
1550-2252
e-ISSN
1550-2252
Number of pages
5
Pages from-to
1-5
Publisher name
Institute of Electrical and Electronics Engineers
Place of publication
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Event location
Washington
Event date
Oct 7, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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