In the last few years, there has been an exponential increase in the usage of the
autonomous vehicles across the globe. It is due to an exponential increase in the popularity …

In the IoT and WSN era, large number of connected objects and sensing devices are
dedicated to collect, transfer, and generate a huge amount of data for a wide variety of fields …

Since the early 1980s, short-term traffic forecasting has been an integral part of most
Intelligent Transportation Systems (ITS) research and applications; most effort has gone into …

The k-nearest neighbor (KNN) model is an effective statistical model applied in short-term
traffic forecasting that can provide reliable data to guide travelers. This study proposes an …

Short-term traffic flow prediction plays a key role of Intelligent Transportation System (ITS),
which supports traffic planning, traffic management and control, roadway safety evaluation …

As the world's population and development increase, the demand for motor-vehicles
increases, adversely impacting the environment and smart cities by increasing traffic …

This paper presents the first hydrological implementation of Emotional Artificial Neural
Network (EANN), as a new generation of Artificial Intelligence-based models for daily rainfall …

Accurate short-term flow forecasting is important for the real-time traffic control, but due to its
complex nonlinear data pattern, getting a high precision is difficult. The support vector …

Reinforcement learning (RL) has been applied to many fields and applications, but there are
still some dilemmas between exploration and exploitation strategy for action selection policy …

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 …