A review of traffic congestion prediction using artificial intelligence
M Akhtar, S Moridpour - Journal of Advanced Transportation, 2021 - Wiley Online Library
In recent years, traffic congestion prediction has led to a growing research area, especially
of machine learning of artificial intelligence (AI). With the introduction of big data by …
of machine learning of artificial intelligence (AI). With the introduction of big data by …
Analysis and management of current road traffic noise
G Rey-Gozalo, JM Barrigón Morillas… - Current Pollution …, 2022 - Springer
Road traffic noise is one of the major environmental pollutants in cities around the world that
continues to increase over the years despite the implementation of regulatory policies. The …
continues to increase over the years despite the implementation of regulatory policies. The …
Hybrid machine learning ensemble techniques for modeling dissolved oxygen concentration
The reliable prediction of dissolved oxygen concentration (DO) is significantly crucial for
protecting the health of the aquatic ecosystem. The current research employed four different …
protecting the health of the aquatic ecosystem. The current research employed four different …
Modelling of traffic noise in the vicinity of urban road intersections
Traffic noise is continuously rising alongside roadways, especially at intersections, due to
rapid urbanization, eventually affecting acoustical climate and quality of life. This present …
rapid urbanization, eventually affecting acoustical climate and quality of life. This present …
Integrating feature extraction approaches with hybrid emotional neural networks for water quality index modeling
The establishment of water quality prediction models is vital for aquatic ecosystems analysis.
The traditional methods of water quality index (WQI) analysis are time-consuming and …
The traditional methods of water quality index (WQI) analysis are time-consuming and …
Deep learning and gradient boosting for urban environmental noise monitoring in smart cities
Every day the innovative IoT technology is expanding further and further in our environment,
with applications deployed in various contexts including cities. Communities can indeed …
with applications deployed in various contexts including cities. Communities can indeed …
[HTML][HTML] Sandstone groundwater salinization modelling using physicochemical variables in Southern Saudi Arabia: Application of novel data intelligent algorithms
Reliable modelling and simulation of groundwater management are crucial for sustainable
development. Groundwater salinization is considered challenging and has recently led to …
development. Groundwater salinization is considered challenging and has recently led to …
Intelligent process optimisation based on cutting-edge emotional learning for performance evaluation of NF/RO of seawater desalination plant
As decision-makers, researchers encounter highly dynamic, complex problems requiring
suitable nature-based and industrial quantitative tools for performance analyses, syntheses …
suitable nature-based and industrial quantitative tools for performance analyses, syntheses …
[HTML][HTML] Enhancing Li+ recovery in brine mining: integrating next-gen emotional AI and explainable ML to predict adsorption energy in crown ether-based hierarchical …
Artificial intelligence (AI) is being employed in brine mining to enhance the extraction of
lithium, vital for the manufacturing of lithium-ion batteries, through improved recovery …
lithium, vital for the manufacturing of lithium-ion batteries, through improved recovery …
Predicting highly dynamic traffic noise using rotating mobile monitoring and machine learning method
Traffic noise, characterized by its highly fluctuating nature, is the second biggest
environmental problem in the world. Highly dynamic noise maps are indispensable for …
environmental problem in the world. Highly dynamic noise maps are indispensable for …