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Predicting Available Parking Slots on Critical and Regular Services by Exploiting a Range of Open Data

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Forecasting
inferredcites →https://doi.org/10.1002/wics.50openalex-snapshot
Neural networks
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Statistical Ideas for Selecting Network Architectures
inferredcites →https://doi.org/10.1007/978-1-4615-5703-6_3openalex-snapshot
The Support Vector Method of Function Estimation
inferredcites →https://doi.org/10.1007/978-3-319-72395-2_58openalex-snapshot
On-Street Car Parking Prediction in Smart City: A Multi-source Data Analysis in Sensor-Cloud Environment
inferredcites →https://doi.org/10.1007/s00778-017-0491-4openalex-snapshot
PACE: a PAth-CEntric paradigm for stochastic path finding
inferredcites →https://doi.org/10.1007/s00778-018-0494-9openalex-snapshot
Risk-aware path selection with time-varying, uncertain travel costs: a time series approach
inferredcites →https://doi.org/10.1016/0304-4076(88)90077-2openalex-snapshot
Regression by local fitting
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Back-propagation neural networks for modeling complex systems
inferredcites →https://doi.org/10.1016/j.egypro.2012.01.221openalex-snapshot
The Model of Parking Demand Forecast for the Urban CCD
inferredcites →https://doi.org/10.1016/j.ejor.2005.02.033openalex-snapshot
Intelligent parking systems
inferredcites →https://doi.org/10.1016/j.eswa.2012.01.091openalex-snapshot
Prediction of parking space availability in real time
inferredcites →https://doi.org/10.1016/j.future.2017.05.001openalex-snapshot
Analysis and assessment of a knowledge based smart city architecture providing service APIs
inferredcites →https://doi.org/10.1016/j.ijforecast.2006.03.001openalex-snapshot
Another look at measures of forecast accuracy
inferredcites →https://doi.org/10.1016/j.jvlc.2014.10.023openalex-snapshot
Km4City ontology building vs data harvesting and cleaning for smart-city services
inferredcites →https://doi.org/10.1016/j.sbspro.2013.05.042openalex-snapshot
Optimal Parking Pricing in General Networks with Provision of Occupancy Information
inferredcites →https://doi.org/10.1016/j.tranpol.2006.05.005openalex-snapshot
Cruising for parking
inferredcites →https://doi.org/10.1016/j.trb.2005.05.003openalex-snapshot
Modeling time-dependent travel choice problems in road networks with multiple user classes and multiple parking facilities
inferredcites →https://doi.org/10.1016/j.trb.2018.04.001openalex-snapshot
How likely am I to find parking? – A practical model-based framework for predicting parking availability
inferredcites →https://doi.org/10.1016/j.trc.2008.07.001openalex-snapshot
The use of space availability information in “PARC” systems to reduce search times in parking facilities
inferredcites →https://doi.org/10.1016/s0169-2070(97)00044-7openalex-snapshot
Forecasting with artificial neural networks:
inferredcites →https://doi.org/10.1021/jm980697nopenalex-snapshot
Robust QSAR Models Using Bayesian Regularized Neural Networks
inferredcites →https://doi.org/10.1023/b:stco.0000035301.49549.88openalex-snapshot
A tutorial on support vector regression
inferredcites →https://doi.org/10.1049/iet-its.2013.0184openalex-snapshot
Short‐term forecasting of available parking space using wavelet neural network model
inferredcites →https://doi.org/10.1080/15472450.2015.1037955openalex-snapshot
A Real-Time Parking Prediction System for Smart Cities
inferredcites →https://doi.org/10.1093/oso/9780198538493.001.0001openalex-snapshot
Neural Networks for Pattern Recognition
inferredcites →https://doi.org/10.1109/72.238311openalex-snapshot
'Neural-gas' network for vector quantization and its application to time-series prediction
inferredcites →https://doi.org/10.1109/icde.2014.6816646openalex-snapshot
Stochastic skyline route planning under time-varying uncertainty
inferredcites →https://doi.org/10.1109/icmlc.2004.1378506openalex-snapshot
Study of the mode of real-time and dynamic parking guidance and information systems based on fuzzy clustering analysis
inferredcites →https://doi.org/10.1109/icnn.1997.614194openalex-snapshot
Gauss-Newton approximation to Bayesian learning
inferredcites →https://doi.org/10.1109/ijcnn.1990.137819openalex-snapshot
Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights
inferredcites →https://doi.org/10.1109/ijcnn.1991.155194openalex-snapshot
Recurrent neural networks and time series prediction
inferredcites →https://doi.org/10.1109/itsc.2003.1252670openalex-snapshot
The research on the key technologies for improving efficiency of parking guidance system
inferredcites →https://doi.org/10.1109/mits.2011.940473openalex-snapshot
SmartParking: A Secure and Intelligent Parking System
inferredcites →https://doi.org/10.1109/smartcomp.2016.7501702openalex-snapshot
Km4City Smart City API: An Integrated Support for Mobility Services
inferredcites →https://doi.org/10.1109/vetecs.2007.69openalex-snapshot
Predicting Parking Lot Occupancy in Vehicular Ad Hoc Networks
inferredcites →https://doi.org/10.1142/s0129183108012467openalex-snapshot
ANALYSIS OF GENERALIZED OPTIMAL CURRENT LATTICE MODEL FOR TRAFFIC FLOW
inferredcites →https://doi.org/10.1145/2452376.2452459openalex-snapshot
iPark
inferredcites →https://doi.org/10.1162/neco.1992.4.3.448openalex-snapshot
A Practical Bayesian Framework for Backpropagation Networks
inferredcites →https://doi.org/10.14778/3021924.3021926openalex-snapshot
Path cost distribution estimation using trajectory data
inferredcites →https://doi.org/10.48550/arxiv.1211.5063openalex-snapshot
On the difficulty of training Recurrent Neural Networks
inferredcites →https://doi.org/10.5555/129449.129452openalex-snapshot
Interpreting neural-network connection weights
inferredcites →https://doi.org/10.5860/choice.31-5500openalex-snapshot
Neural networks for pattern recognition

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Statistics vs Machine Learning for Modelling Parking Systems: How the Idiosyncrasies of Each Method are Reflected in the Model Forecast
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Spatio-Temporal Clustering for Optimal Real-Time Parking Availability Estimation
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Real-Time Parking Availability Classification on a Large-Area Scale
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Enhancing Urban Mobility with Predictive Parking Occupancy Analysis
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Deep Learning Based Parking Prediction Using LSTM Approach
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Parking slot occupancy prediction using LSTM
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Predicting vacant parking space availability zone-wisely: a hybrid deep learning approach
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Predicting parking occupancy via machine learning in the web of things
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Data-Driven Robust Optimal Allocation of Shared Parking Spaces Strategy Considering Uncertainty of Public Users’ and Owners’ Arrival and Departure: An Agent-Based Approach
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Deep Learning for Short-Term Prediction of Available Bikes on Bike-Sharing Stations
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Parking Occupancy Prediction Method Based on Multi Factors and Stacked GRU-LSTM
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Vehicular Traffic Flow Reconstruction Analysis to Mitigate Scenarios With Large City Changes
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Predicting Free Parking Slots via Deep Learning in Short-Mid Terms Explaining Temporal Impact of Features
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Evaluation of Machine Learning Algorithms for the Prediction of Simulated Company Parking Space Occupancy
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Optimizing Campus Parking and Reducing Congestion Through Machine Learning
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On-Street Parking Prediction: A Comparative Study
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A Stacked Long Short-Term Memory Neural Networks for Parking Occupancy Rate Prediction
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