Predicting Free Parking Slots via Deep Learning in Short-Mid Terms Explaining Temporal Impact of Features-Reference-Cited by-同舟云学术

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Predicting Free Parking Slots via Deep Learning in Short-Mid Terms Explaining Temporal Impact of Features

Published:2023 Issue: Volume:11 Page:101678-101693
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Bilotta Stefano¹^ORCID,Ipsaro Palesi Luciano Alessandro¹^ORCID,Nesi Paolo¹^ORCID

Affiliation:

1. Department of Information Engineering, Distributed Systems and Internet Technologies Laboratory, University of Florence, Florence, Italy

Funder

Ministero Industria Università e Ricerca (MIUR), University of Florence

National Center on Sustainable Mobility, Centro Nazionale MObilità SosTenibile

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10247516.pdf?arnumber=10247516

Reference66 articles.

1. Short-Term Forecasting of Off-Street Parking Occupancy

2. On the difficulty of training recurrent neural networks;pascanu;Proc Int Conf Mach Learn,2013

3. Optimal Parking Pricing in General Networks with Provision of Occupancy Information

4. Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights

5. Assessing the Predictive Value of Traffic Count Data in the Imputation of On-Street Parking Occupancy in Amsterdam

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3. Dynamic Spatio-Temporal Adaptive Graph Convolutional Recurrent Networks for Vacant Parking Space Prediction;Applied Sciences;2024-07-07

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