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Parking prediction in smart cities: A survey
With the growing number of cars in cities, smart parking is gradually becoming a strategic
issue in building a smart city. As the precondition in smart parking, accurate parking …
issue in building a smart city. As the precondition in smart parking, accurate parking …
Parking occupancy prediction method based on multi factors and stacked GRU-LSTM
C Zeng, C Ma, K Wang, Z Cui - Ieee Access, 2022 - ieeexplore.ieee.org
With the development of society and the continuous advancement of urbanization, motor
vehicles have increased rapidly, which exacerbates the imbalance between parking supply …
vehicles have increased rapidly, which exacerbates the imbalance between parking supply …
Parking availability prediction for sensor-enabled car parks in smart cities
Y Zheng, S Rajasegarar… - 2015 IEEE tenth …, 2015 - ieeexplore.ieee.org
The growth in low-cost, low-power sensing and communication technologies is creating a
pervasive network infrastructure called the Internet of Things (IoT), which enables a wide …
pervasive network infrastructure called the Internet of Things (IoT), which enables a wide …
Parking demand forecasting based on improved complete ensemble empirical mode decomposition and GRU model
G Li, X Zhong - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Parking demand forecasting plays an important role in relieving traffic congestion and
reducing greenhouse gas emissions. However, most previous studies model based on …
reducing greenhouse gas emissions. However, most previous studies model based on …
A survey of parking solutions for smart cities
Existing surveys look at parking solutions from the perspective of sensors, communication
protocols, and the hardware-software interface. While this is a worthwhile approach, it …
protocols, and the hardware-software interface. While this is a worthwhile approach, it …
[HTML][HTML] Predicting parking occupancy via machine learning in the web of things
Abstract The Web of Things (WoT) enables information gathered by sensors deployed in
urban environments to be easily shared utilizing open Web standards and semantic …
urban environments to be easily shared utilizing open Web standards and semantic …
Predicting electric vehicle charging station availability using ensemble machine learning
Electric vehicles may reduce greenhouse gas emissions from individual mobility. Due to the
long charging times, accurate planning is necessary, for which the availability of charging …
long charging times, accurate planning is necessary, for which the availability of charging …
A user behavior and reinforcement learning based dynamic pricing method for idle connection time reduction at charging stations
Reducing idle connection time is crucial for improving the operational efficiency of charging
stations and enhancing the satisfaction of electric vehicle (EV) users. During idle connection …
stations and enhancing the satisfaction of electric vehicle (EV) users. During idle connection …
Analysis of user charging behavior at public charging stations
Plug-in electric vehicles (PEVs) play significant role in the development of green cities, since
they have less impact on the environment compared to conventional vehicles. To promote …
they have less impact on the environment compared to conventional vehicles. To promote …
Prediction of Vacant Parking Spaces in Multiple Parking Lots: A DWT-ConvGRU-BRC Model
L Gao, W Fan, Z Hu, W Jian - Applied Sciences, 2023 - mdpi.com
For cities, the problem of “difficult parking and chaotic parking” increases carbon emissions
and reduces quality of life. Accurately and efficiently predicting the availability of vacant …
and reduces quality of life. Accurately and efficiently predicting the availability of vacant …