[HTML][HTML] A Review of multi-source data fusion and analysis algorithms in smart city construction: Facilitating real estate management and urban optimization
B Liu, Q Li, Z Zheng, Y Huang, S Deng, Q Huang, W Liu - Algorithms, 2025 - mdpi.com
In the context of the booming construction of smart cities, multi-source data fusion and
analysis algorithms play a key role in optimizing real estate management and improving …
analysis algorithms play a key role in optimizing real estate management and improving …
Urbankg: An urban knowledge graph system
Every day, our living city produces a tremendous amount of spatial-temporal data, involved
with multiple sources from the individual scale to the city scale. Undoubtedly, such massive …
with multiple sources from the individual scale to the city scale. Undoubtedly, such massive …
Domain adversarial graph neural network with cross-city graph structure learning for traffic prediction
Deep learning models have emerged as a promising way for traffic prediction. However, the
requirement for large amounts of training data remains a significant issue for achieving well …
requirement for large amounts of training data remains a significant issue for achieving well …
UUKG: unified urban knowledge graph dataset for urban spatiotemporal prediction
Abstract Accurate Urban SpatioTemporal Prediction (USTP) is of great importance to the
development and operation of the smart city. As an emerging building block, multi-sourced …
development and operation of the smart city. As an emerging building block, multi-sourced …
Research on application of knowledge graph in industrial control system security situation awareness and decision-making: A survey
L Liu, P Xu, K Fan, M Wang - Neurocomputing, 2024 - Elsevier
Abstract Knowledge graph as a powerful tool for knowledge organization and
representation, can integrate scattered data into a unified knowledge network, enabling …
representation, can integrate scattered data into a unified knowledge network, enabling …
Knowledge-infused contrastive learning for urban imagery-based socioeconomic prediction
Monitoring sustainable development goals requires accurate and timely socioeconomic
statistics, while ubiquitous and frequently-updated urban imagery in web like satellite/street …
statistics, while ubiquitous and frequently-updated urban imagery in web like satellite/street …
Hierarchical knowledge graph learning enabled socioeconomic indicator prediction in location-based social network
Socioeconomic indicators reflect location status from various aspects such as
demographics, economy, crime and land usage, which play an important role in the …
demographics, economy, crime and land usage, which play an important role in the …
SLAFusion: Attention fusion based on SAX and LSTM for dangerous driving behavior detection
Dangerous driving behaviors are the main cause of most traffic accidents, and the detection
of these behaviors is one of the extremely important researches in Intelligent Transportation …
of these behaviors is one of the extremely important researches in Intelligent Transportation …
FedDAF: Federated deep attention fusion for dangerous driving behavior detection
Dangerous driving behavior detection is one of the most important researches in Intelligent
Transportation System (ITS), which can effectively reduce the probability and number of …
Transportation System (ITS), which can effectively reduce the probability and number of …
Landslide displacement prediction via attentive graph neural network
Landslides are among the most common geological hazards that result in considerable
human and economic losses globally. Researchers have put great efforts into addressing …
human and economic losses globally. Researchers have put great efforts into addressing …