A survey of UAV-based data collection: Challenges, solutions and future perspectives

K Messaoudi, OS Oubbati, A Rachedi, A Lakas… - Journal of network and …, 2023‏ - Elsevier
Abstract Internet of Things (IoT) generates unlimited data, which should be collected and
forwarded towards a central controller (CC) for further processing and decision-making …

Explainable artificial intelligence applications in cyber security: State-of-the-art in research

Z Zhang, H Al Hamadi, E Damiani, CY Yeun… - IEEe …, 2022‏ - ieeexplore.ieee.org
This survey presents a comprehensive review of current literature on Explainable Artificial
Intelligence (XAI) methods for cyber security applications. Due to the rapid development of …

A hybrid deep learning based traffic flow prediction method and its understanding

Y Wu, H Tan, L Qin, B Ran, Z Jiang - Transportation Research Part C …, 2018‏ - Elsevier
Deep neural networks (DNNs) have recently demonstrated the capability to predict traffic
flow with big data. While existing DNN models can provide better performance than shallow …

Temporal multi-graph convolutional network for traffic flow prediction

M Lv, Z Hong, L Chen, T Chen… - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
Traffic flow prediction plays an important role in ITS (Intelligent Transportation System). This
task is challenging due to the complex spatial and temporal correlations (eg, the constraints …

Advanced optimizer for maximum power point tracking of photovoltaic systems in smart grid: A roadmap towards clean energy technologies

S Zheng, M Shahzad, HM Asif, J Gao, HA Muqeet - Renewable Energy, 2023‏ - Elsevier
With the increased load demand and generation cost of electricity, renewable energy
sources (RES) provide cost effective and environment-friendly solution. Integration of solar …

Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook

X Zou, Y Yan, X Hao, Y Hu, H Wen, E Liu, J Zhang… - Information …, 2025‏ - Elsevier
As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for
sustainable development by harnessing the power of cross-domain data fusion from diverse …

Traffic flow optimization using a quantum annealer

F Neukart, G Compostella, C Seidel, D Von Dollen… - Frontiers in …, 2017‏ - frontiersin.org
Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for
solving binary optimization problems. Hardware implementations of quantum annealing …

Survey on traffic prediction in smart cities

AM Nagy, V Simon - Pervasive and Mobile Computing, 2018‏ - Elsevier
The rapid development in machine learning and in the emergence of new data sources
makes it possible to examine and predict traffic conditions in smart cities more accurately …

Trajectory data mining: an overview

Y Zheng - ACM Transactions on Intelligent Systems and …, 2015‏ - dl.acm.org
The advances in location-acquisition and mobile computing techniques have generated
massive spatial trajectory data, which represent the mobility of a diversity of moving objects …

Multistep speed prediction on traffic networks: A deep learning approach considering spatio-temporal dependencies

Z Zhang, M Li, X Lin, Y Wang, F He - Transportation research part C …, 2019‏ - Elsevier
Multistep traffic forecasting on road networks is a crucial task in successful intelligent
transportation system applications. To capture the complex non-stationary temporal …