Optimising logistics in intelligent transportation systems through CNN-IT: a convolutional neural network approach for enhanced efficiency and precision-Reference-Cited by-同舟云学术

Optimising logistics in intelligent transportation systems through CNN-IT: a convolutional neural network approach for enhanced efficiency and precision

Published:2024-03-24 Issue: Volume: Page:1-13
ISSN:0954-4828
Container-title:Journal of Engineering Design
language:en
Short-container-title:Journal of Engineering Design

Author:

Wang Xinghe¹²,Chipusu Kavimbi³,Lin Chaoquan²,Chen Jiabin¹,Liu Bihua⁴

Affiliation:

1. School of Intelligent Manufacturing Engineering, Liming Vocational University, Quanzhou, People’s Republic of China

2. Pusat Technology Pengajaran & Multimedia, Universiti Sains Malaysia, George Town, Malaysia

3. Department of Traffic and Transportation Engineering, Central South University, Changsha, People’s Republic of China

4. School of Design, Fujian University of Technology, Fuzhou, People’s Republic of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/09544828.2024.2333196

Reference25 articles.

1. Two-stage Intrusion Detection System in Intelligent Transportation Systems Using Rule Extraction Methods from Deep Neural Networks;Almutlaq Samah;IEEE Transactions on Intelligent Transportation Systems,2022

2. Transportation Mode Detection by Embedded Sensors Based on Ensemble Learning

3. Image analysis and rule-based reasoning for a traffic monitoring system

4. A deep convolutional neural network based approach for vehicle classification using large-scale GPS trajectory data

5. Didavi, A. B., R. G. Agbokpanzo, and M. Agbomahena. 2021. “Comparative Study of Decision Tree, Random Forest and XGBoost Performance in Forecasting the Power Output of a Photovoltaic System.” 2021 4th International Conference on Bio-Engineering for Smart Technologies (BioSMART), IEEE.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Symmetry-Enhanced LSTM-Based Recurrent Neural Network for Oscillation Minimization of Overhead Crane Systems during Material Transportation;Symmetry;2024-07-18