แจ้งเอกสารไม่ครบถ้วน, ไม่ตรงกับชื่อเรื่อง หรือมีข้อผิดพลาดเกี่ยวกับเอกสาร ติดต่อที่นี่ ==>
หากไม่มีอีเมลผู้รับให้กรอก thailis-noc@uni.net.th
หากไม่มีอีเมลผู้รับให้กรอก thailis-noc@uni.net.th
Kumar, Manish. Accurate and decentralized approach for traffic flow prediction using federated learning. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2023.
Accurate and decentralized approach for traffic flow prediction using federated learning
Name: Maurya, Manish Kumar
Organization :
Indian Institute of Information Technology Allahabad. Dept. of Information Technology
Email :
pwc2017002@iiita.ac.in
Name: Kumar, Manish
Organization :
Indian Institute of Information Technology Allahabad. Dept. of Information Technology
Email :
manish@iiita.ac.in
keyword:
Federated Learning
LCSH:
Traffic congestion
-- Forecasting
;
Privacy
LCSH:
Arhus City
Abstract:
Traffic prediction involves forecasting the density
and flow of traffic, primarily aimed at efficiently managing
vehicular movements in a highly congested urban environment.
Its purpose is to offer valuable insights for reducing traffic
congestion and devising optimal routes that minimize energy
consumption and travel time. Nevertheless, conventional traffic
prediction faces a significant challenge: the need to store data
when making predictions, resulting in increased latency, prolonged
training time, and the consumption of expensive storage
resources. Moreover, sharing such data for training may raise
privacy concerns due to the potential inclusion of sensitive
information. To address these issues, this paper adopts Federated
Learning (FL) to train the prediction model closer to the data
sources. To assess the effectiveness of the proposed approach,
real-world traffic data from Arhus City has been employed.
The proposed methods prediction accuracy has been evaluated
compared to a centralized approach
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2023
Modified:
2024-04-23
Issued:
2024-04-23
บทความ/Article
application/pdf
BibliograpyCitation :
In Institute of Electrical and Electronics Engineers. The 27th International Computer Science and Engineering Conference 2023 (ICSEC 2023) (pp.287-292). Bangkok : Institute of Electrical and Electronics Engineers
eng
©copyrights King Mongkut's University of Technology North Bangkok
RightsAccess:
ใช้เวลา
0.036503 วินาที
Maurya, Manish Kumar
| Title | Contributor | Type |
|---|---|---|
| Accurate and decentralized approach for traffic flow prediction using federated learning
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Maurya, Manish Kumar;Kumar, Manish | บทความ/Article |
Kumar, Manish
| Title | Contributor | Type |
|---|---|---|
| Accurate and decentralized approach for traffic flow prediction using federated learning
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Maurya, Manish Kumar;Kumar, Manish | บทความ/Article | |
| Machine learning based classification of academic stress factors
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Bhatia, Kashish;Kumar, Manish;Bhatia, Rajesh Kumar;Sharma, Aakankasha;Chhabra, Krittika | บทความ/Article | |
| FPGA based design of multifunction ALU
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kumar, Anup;Kumar, Manish;Jha, Gouri Shankar;Suneja, Kriti | บทความ/Article | |
| Stacking ensemble-based automatic web page classification
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Deeksha;Bhatia, Rajesh;Bhardwaj, Shikhar;Kumar, Manish;Bhatia, Kashish;Gill, Shabeg Singh | บทความ/Article |