Prediction of Traffic Volume Based on Deep Learning Model for AADT Correction

Accurate traffic volume data are crucial for effective traffic management, infrastructure development, and demand forecasting. This study addresses the challenges associated with traffic volume data collection, including, notably, equipment malfunctions that often result in missing data and inadequa...

詳細記述

書誌詳細

出版年:	Applied Sciences
第一著者:	Dae Cheol Han
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2024-10-01
主題:	annual average daily traffic volume (AADT) traffic volume long short-term memory (LSTM) power function deep learning
オンライン･アクセス:	https://www.mdpi.com/2076-3417/14/20/9436