Abstract
We propose a deep learning model that can pre-dict future traffic. The proposed Transformer-based model is evaluated using the visit data of popular Wikipedia pages for more than 2 years through multiple accessing devices such as mobile and desktop. The experiment results demonstrate that the proposed model can predict the future traffic with high accuracy.
| Original language | English |
|---|---|
| Title of host publication | 2022 IEEE International Conference on Consumer Electronics, ICCE 2022 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781665441544 |
| DOIs | |
| Publication status | Published - 2022 |
| Externally published | Yes |
| Event | 2022 IEEE International Conference on Consumer Electronics, ICCE 2022 - Virtual, Online, United States Duration: 2022 Jan 7 → 2022 Jan 9 |
Publication series
| Name | Digest of Technical Papers - IEEE International Conference on Consumer Electronics |
|---|---|
| Volume | 2022-January |
| ISSN (Print) | 0747-668X |
Conference
| Conference | 2022 IEEE International Conference on Consumer Electronics, ICCE 2022 |
|---|---|
| Country/Territory | United States |
| City | Virtual, Online |
| Period | 22/1/7 → 22/1/9 |
Bibliographical note
Funding Information:ACKNOWLEDGMENT This research was supported by National Research Foundation (NRF) of Korea Grant funded by the Korean Government (MSIT) (No. 2021R1A4A3022102) and the MSIT (Ministry of Science and ICT), Korea, under the ICAN (ICT Challenge and Advanced Network of HRD) program (IITP-2021-2020-0-01816) supervised by the IITP (Institute of Information & Communications Technology Planning & Evaluation).
Funding Information:
This research was supported by National Research Foundation (NRF) of Korea Grant funded by the Korean Government (MSIT) (No. 2021R1A4A3022102).
Publisher Copyright:
© 2022 IEEE.
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering