A survey of traffic prediction: from spatio-temporal data to intelligent transportation
Intelligent transportation (eg, intelligent traffic light) makes our travel more convenient and
efficient. With the development of mobile Internet and position technologies, it is reasonable …
efficient. With the development of mobile Internet and position technologies, it is reasonable …
Applications of deep reinforcement learning in communications and networking: A survey
This paper presents a comprehensive literature review on applications of deep
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Deep learning for air pollutant concentration prediction: A review
Air pollution has become one of the critical environmental problem in the 21st century and
has attracted worldwide attentions. To mitigate it, many researchers have investigated the …
has attracted worldwide attentions. To mitigate it, many researchers have investigated the …
Air-pollution prediction in smart city, deep learning approach
Over the past few decades, due to human activities, industrialization, and urbanization, air
pollution has become a life-threatening factor in many countries around the world. Among …
pollution has become a life-threatening factor in many countries around the world. Among …
Neural network guided interpolation for mapping canopy height of China's forests by integrating GEDI and ICESat-2 data
Spatially continuous estimates of forest canopy height at national to global scales are critical
for quantifying forest carbon storage, understanding forest ecosystem processes, and …
for quantifying forest carbon storage, understanding forest ecosystem processes, and …
The IoT for smart sustainable cities of the future: An analytical framework for sensor-based big data applications for environmental sustainability
SE Bibri - Sustainable cities and society, 2018 - Elsevier
Abstract The Internet of Things (IoT) is one of the key components of the ICT infrastructure of
smart sustainable cities as an emerging urban development approach due to its great …
smart sustainable cities as an emerging urban development approach due to its great …
State-of-the-art deep learning: Evolving machine intelligence toward tomorrow's intelligent network traffic control systems
Currently, the network traffic control systems are mainly composed of the Internet core and
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …
Machine learning algorithms to forecast air quality: a survey
Air pollution is a risk factor for many diseases that can lead to death. Therefore, it is
important to develop forecasting mechanisms that can be used by the authorities, so that …
important to develop forecasting mechanisms that can be used by the authorities, so that …
Long short-term memory-Fully connected (LSTM-FC) neural network for PM2. 5 concentration prediction
People have been suffering from air pollution for a decade in China, especially from PM 2.5
(particulate matter with a diameter of less than 2.5 μm). Accurate prediction of air quality has …
(particulate matter with a diameter of less than 2.5 μm). Accurate prediction of air quality has …