This review explores the application of Long Short-Term Memory (LSTM) networks, a
specialized type of recurrent neural network (RNN), in the field of polymeric sciences. LSTM …

Widespread traffic congestion significantly impacts the quality of life, posing several
problems and challenges. To reduce traffic congestion, it is necessary to have accurate …

This paper presents an integral lattice hydrodynamic model to examine the impact of driver's
anticipation and driving prediction with density deviation of leading vehicle under passing …

Electronic throttle control (ETC), a mechanism for precise regulation of engine power and
torque production, is a typical component in modern automobiles. Little research has been …

Accurate forecasting information of short-term subway passenger flow is an important
scientific reference for daily operations and urban management. The rapid time-varying …

Reliable traffic flow data is not only crucial for traffic management and planning, but also the
foundation for many intelligent applications. However, the phenomenon of missing traffic …

Adverse weather conditions significantly influence traffic flow dynamics, posing challenges
for safe and efficient transportation systems. This study proposes a novel car-following …

In order to improve the accuracy of concrete dynamic principal identification, a concrete
dynamic principal identification model based on Improved Dung Beetle Algorithm (IDBO) …

Objectives: In order to control and manage the traffic flow in contexts of congestion, real-time
highway traffic flow models play a significant role in intelligent transportation system. The …

In intelligent transportation systems, short-term traffic flow prediction, as a core component,
plays a crucial role in improving the operational efficiency and safety of the transportation …