A hybrid model for predicting the energy dissipation on the block ramp hydraulic structures

M Rahmanshahi, J Jafari-Asl, M Shafai Bejestan… - Water Resources …, 2023 - Springer
Block ramps are among the environmentally friendly hydraulic structures used for energy
dissipation in rivers and waterways. Modeling the energy dissipation on these structures is …

[HTML][HTML] SVD-based adaptive fuzzy for generalized transportation

MR Aljanabi, K Borna, S Ghanbari, AJ Obaid - Alexandria Engineering …, 2024 - Elsevier
This research stems from the urgent need to address the complex challenges faced in
multimodal transportation within the cargo sector, particularly concerning the reduction of …

[HTML][HTML] Intelligent meta-heuristic-based optimization of traffic light timing using artificial intelligence techniques

MA Khasawneh, A Awasthi - Electronics, 2023 - mdpi.com
This research examines worldwide concerns over traffic congestion, encompassing aspects
such as security, parking, pollution, and congestion. It specifically emphasizes the …

SDVN Enabled Traffic Light Cooperative Framework for E-SIoV Mobility in a Smart City Scenario

A Sachan, N Kumar - IEEE Transactions on Vehicular …, 2024 - ieeexplore.ieee.org
The Social Internet of Vehicles (SIoVs) is an advanced approach to vehicular networking
that connects specialized vehicles to share and exchange information, such as traffic jams …

S-Edge: heterogeneity-aware, light-weighted, and edge computing integrated adaptive traffic light control framework

A Sachan, N Kumar - The Journal of Supercomputing, 2023 - Springer
Rapid increase in the private and public vehicles fleet causes urban centers heavily
populated with limited transport road infrastructure. To overcome this, in real-time scenarios …

Congestion minimization using fog-deployed DRL-agent feedback enabled traffic light cooperative framework

A Sachan, NS Chauhan… - 2023 IEEE/ACM 23rd …, 2023 - ieeexplore.ieee.org
Congestion at signalized intersections can be alleviated by improving traffic signal control
system's performance. In this context, Deep Reinforcement Learning (DRL) methods are …

Towards optimal tuned machine learning techniques based vehicular traffic prediction for real roads scenarios

R Qaddoura, MB Younes, A Boukerche - Ad Hoc Networks, 2024 - Elsevier
Smart cities have been widely investigated, and several algorithms, techniques, and
protocols have recently been developed to serve smart city environments. Intelligent traffic …

Multi‐criteria evolutionary optimization of a traffic light using genetics algorithm and teaching‐learning based optimization

H Yektamoghadam, A Nikoofard, M Behzadi… - Expert …, 2024 - Wiley Online Library
Today, the development of urbanization and increasing the number of vehicles has resulted
in displeased consequences like traffic congestion and vehicle queuing. The vast majority of …

Measurement and analysis of heterogeneous road transport parameters using Smart Traffic Analyzer and SUMO Simulator: An experimental approach

S Ravindran, GB Balachandran, PW David - Measurement, 2025 - Elsevier
The main objective of research work is to study the characteristics of heterogeneous road
transport environment & compare its dynamic parameters with the performance metrics …

An Applied Type-3 Fuzzy Controller for Gyroscopes

S Li, A Mohammadzadeh, C Zhang - International Journal of Fuzzy …, 2025 - Springer
Gyroscopes play a crucial role in an extensive range of applications such as navigation
systems, motion control, virtual reality, and many electronic devices. The efficiency of …