Paper-Conference

Comparative Analysis of Deep Learning and Large Language Models in Time Series Traffic Flow Prediction
This research compares the performance of deep learning models and large language models in a time series traffic flow prediction. The …
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GeoAggregator: An Efficient Transformer Model for Geo-Spatial Tabular Data
Modeling geospatial tabular data with deep learning has become a promising alternative to traditional statistical and machine learning …
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A Transformer-Based Model for Effective Representation of Geospatial Data and Context
Machine learning (ML) and Artificial Intelligence (AI) models have been increasingly adopted for geospatial tasks. However, geospatial …
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27th AGILE Conference on Geographic Information Science \"Geographic Information Science for a Sustainable Future\"
No abstract available.
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Analysis The Influencing Factors of Urban Traffic Flows by Using Emerging Urban Big Data
This research applies spatial Durbin model to analyse traffic flow distributions via various factors in the urban areas and traffic …
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Analysis the Influencing Factors of Urban Traffic Flows by Using New and Emerging Urban Big Data and Deep Learning
Urban traffic analysis has acted an important role in the process of urban development, which can provide insights for urban planning, …
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Bridging the Gap Between Geography and Marketing: Opportunities for CyberGIS
No abstract available.
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