[HTML][HTML] Smart city concept in the light of the literature review
Aguilar, AG, & López, FM (2016). Espacios de pobreza en la periferia urbana y suburbios
interiores de la Ciudad de México. Las desventajas acumuladas [Poverty spaces in the …
interiores de la Ciudad de México. Las desventajas acumuladas [Poverty spaces in the …
[HTML][HTML] Data mining algorithms for smart cities: A bibliometric analysis
A Kousis, C Tjortjis - Algorithms, 2021 - mdpi.com
Smart cities connect people and places using innovative technologies such as Data Mining
(DM), Machine Learning (ML), big data, and the Internet of Things (IoT). This paper presents …
(DM), Machine Learning (ML), big data, and the Internet of Things (IoT). This paper presents …
On region-level travel demand forecasting using multi-task adaptive graph attention network
Accurate travel demand forecasting at the regional level benefits to urban traffic
management and service operations. Irregular regions can be naturally represented by …
management and service operations. Irregular regions can be naturally represented by …
Urban human mobility: Data-driven modeling and prediction
Human mobility is a multidisciplinary field of physics and computer science and has drawn a
lot of attentions in recent years. Some representative models and prediction approaches …
lot of attentions in recent years. Some representative models and prediction approaches …
Big trajectory data: A survey of applications and services
The rapid development of wireless infrastructure and data acquisition technologies
contributes to the explosive growth of data, especially trajectory data with rich information …
contributes to the explosive growth of data, especially trajectory data with rich information …
Spatio-temporal trajectory similarity learning in road networks
Deep learning based trajectory similarity computation holds the potential for improved
efficiency and adaptability over traditional similarity computation. However, existing learning …
efficiency and adaptability over traditional similarity computation. However, existing learning …
Travel time prediction: Based on gated recurrent unit method and data fusion
Travel time prediction is the basis for the implementation of advanced traveler information
systems and advanced transport management systems in intelligent transportation systems …
systems and advanced transport management systems in intelligent transportation systems …
Truck traffic speed prediction under non-recurrent congestion: Based on optimized deep learning algorithms and GPS data
J Zhao, Y Gao, Z Yang, J Li, Y Feng, Z Qin, Z Bai - IEEE Access, 2019 - ieeexplore.ieee.org
Due to the restriction of traffic management measure in large cities, large heavy-haul trucks
can only travel on the circuits and expressways around the city, which often causes …
can only travel on the circuits and expressways around the city, which often causes …
[HTML][HTML] Quantitative identification of urban functions with fishers' exact test and POI data applied in classifying urban districts: A case study within the sixth ring road in …
D Yi, J Yang, J Liu, Y Liu, J Zhang - ISPRS International Journal of Geo …, 2019 - mdpi.com
Urban areas involve different functions that attract individuals and fit personal needs.
Understanding the distribution and combination of these functions in a specific district is …
Understanding the distribution and combination of these functions in a specific district is …
Representation learning for short text clustering
Effective representation learning is critical for short text clustering due to the sparse, high-
dimensional and noise attributes of short text corpus. Existing pre-trained models (eg …
dimensional and noise attributes of short text corpus. Existing pre-trained models (eg …