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A survey of UAV-based data collection: Challenges, solutions and future perspectives
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 …
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
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 …
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
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 …
flow with big data. While existing DNN models can provide better performance than shallow …
Temporal multi-graph convolutional network for traffic flow prediction
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 …
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
With the increased load demand and generation cost of electricity, renewable energy
sources (RES) provide cost effective and environment-friendly solution. Integration of solar …
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
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 …
sustainable development by harnessing the power of cross-domain data fusion from diverse …
Traffic flow optimization using a quantum annealer
Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for
solving binary optimization problems. Hardware implementations of quantum annealing …
solving binary optimization problems. Hardware implementations of quantum annealing …
Survey on traffic prediction in smart cities
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 …
makes it possible to examine and predict traffic conditions in smart cities more accurately …
Trajectory data mining: an overview
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 …
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
Multistep traffic forecasting on road networks is a crucial task in successful intelligent
transportation system applications. To capture the complex non-stationary temporal …
transportation system applications. To capture the complex non-stationary temporal …