AIMC Topic: Transportation

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Empirical study of daily link traffic volume forecasting based on a deep neural network.

PloS one
Forecasting the daily link traffic volume is critical in transportation demand analysis in feasibility studies for planning transportation facilities. The high purchase and maintenance cost of commercial transport planning software poses a challenge ...

Non-end-to-end adaptive graph learning for multi-scale temporal traffic flow prediction.

PloS one
Accurate traffic flow prediction is vital for intelligent transportation systems but presents significant challenges. Existing methods, however, have the following limitations: (1) insufficient exploration of interactions across different temporal sc...

The urban physical environment and leisure-time physical activity in early midlife: a FinnTwin12 study.

Health & place
Under the exposome framework, this study examined the relationship between the urban physical environment and leisure-time physical activity during early midlife based on 394 participants (mean age: 37, range 34-40) from the FinnTwin12 cohort, residi...

Exploring the drivers of digital transformation in Chinese port and shipping enterprises: A machine learning approach.

PloS one
With the transition to a global green low-carbon economy, the urgency for digital transformation in the port and shipping industry has become increasingly prominent in making enterprises more efficient and sustainable. This study focuses on how Chine...

The analysis of rural revitalization serviceplatform in smart city under back propagation neural network.

PloS one
To achieve rural revitalization and enhance the development of rural tourism, this study employs a back propagation neural network (BPNN) to construct a rural revitalization development model. Additionally, the Grey Relation Analysis (GRA) algorithm ...

Toward a conceptual model to improve the user experience of a sustainable and secure intelligent transport system.

Acta psychologica
The rapid advancement of automotive technologies has spurred the development of innovative applications within intelligent transportation systems (ITS), aimed at enhancing safety, efficiency and sustainability. These applications, such as advanced dr...

Uncovering soil heavy metal pollution hotspots and influencing mechanisms through machine learning and spatial analysis.

Environmental pollution (Barking, Essex : 1987)
Soil heavy metal (HM) pollution is a significant and widespread environmental issue in China, highlighting the need to quantify influencing factors and identify priority concern areas for effective prevention and management. Based on published litera...

Subway opening enables urban green development: Evidence from difference-in-differences and double dual machine learning methods.

Journal of environmental management
Urban rail transport is an important part of transport infrastructure, which is significant in empowering green-oriented urban development. However, few studies in the existing literature explore the effect of subway opening on urban green developmen...

Safety After Dark: A Privacy Compliant and Real-Time Edge Computing Intelligent Video Analytics for Safer Public Transportation.

Sensors (Basel, Switzerland)
Public transportation systems play a vital role in modern cities, but they face growing security challenges, particularly related to incidents of violence. Detecting and responding to violence in real time is crucial for ensuring passenger safety and...