Predicting Estimated Time of Arrival Using Boosting Models-Reference-Cited by-同舟云学术

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Predicting Estimated Time of Arrival Using Boosting Models

Published:2024-02-19 Issue: Volume:2 Page:467-472
ISSN:
Container-title:2024 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)
language:
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Author:

Kam Say-Hong¹,Chong Yung-Wey²,Ibrahim Noor Farizah¹,Keoh Sye-Loong³,Phon-Amnuaisuk Somnuk⁴,Abdul Rahim Sharul Kamal⁵

Affiliation:

1. School of Computer Sciences, Universiti Sains Malaysia,Penang,Malaysia

2. National Advanced IPv6 Centre, Universiti Sains Malaysia,Penang,Malaysia

3. School of Computing Science, University of Glasgow,Glasgow,United Kingdom

4. School of Computing and Informatics, Universiti Teknologi Brunei,Brunei,Brunei

5. Universiti Teknologi Malaysia,Faculty of Electrical Engineering,Johor,Malaysia

Funder

Keio University

APNIC Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10463165/10463194/10463273.pdf?arnumber=10463273

Reference24 articles.

1. Proclivity of university students to use public bus transport service;Soh,2014

2. rrnrrrrn;SHAFIE;HOCHSCHULE KARLSRUHE TECHNIK UND WIRTSCHAFT,2016

3. A Technique of Filtering Dirty Data Based on Temporal- Spatial Correlation in Wireless Sensor Network

4. Multi-output bus travel time prediction with convolutional LSTM neural network

5. Predictive analytics on open big data for supporting smart transportation services

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