Machine learning (ML) and deep learning (DL) have become very popular in the research
community for addressing complex issues in intelligent transportation. This has resulted in …

While predicting parking occupancy is crucial for managing urban congestion, existing
models often exhibit gaps in accuracy, uncertainty handling, and integration potential. This …

To address the parking challenges, this survey delves into the significant impact of machine
learning (ML) on parking availability (PA) predictions. With swelling urban populations …

Student success is crucial to the process of building a Cross-border e-commerce (CBEC)
talent development platform. Analysis of the important aspects impacting performance and …

Cruising-for-parking in an urban area is a time-consuming and frustrating activity. We
present four machine learning-based models to predict the parking availability of street …

The carbon emission of fuel vehicles is a major consideration that affects the dual carbon
goal in urban traffic. The problem of “difficult parking and disorderly parking” in static traffic …

As cities grow denser, the need for sustainable urban transport solutions intensifies.
Effective management of on-street parking is critical in addressing traffic congestion and …

Finding a parking space is a major concern in megacities, causing drivers to lose time and
money while contributing to atmospheric pollution and global warming. This study proposes …

Accurate prediction of parking spaces plays a crucial role in maximizing the efficiency of
parking resources and optimizing traffic conditions. However, the majority of earlier research …

Given a tweet, a machine learning model when after undertaking the training, development
and testing phase is able to predict where the author of the tweet is situated. Our notion is …