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Unobserved Component Model for Predicting Monthly Traffic Volume

https://doi.org/10.1061/jtepbs.0000281
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Mann‐Whitney U Test
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Short‐term traffic flow prediction with linear conditional Gaussian Bayesian network
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Estimation procedures for structural time series models
inferredcites →https://doi.org/10.1007/11550907_43openalex-snapshot
Traffic Flow Forecasting Using a Spatio-temporal Bayesian Network Predictor
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Recursive Estimation and Time-Series Analysis
inferredcites →https://doi.org/10.1007/s11063-015-9409-6openalex-snapshot
A Short-term Traffic Flow Forecasting Method Based on the Hybrid PSO-SVR
inferredcites →https://doi.org/10.1007/s12544-015-0170-8openalex-snapshot
Short-term traffic flow prediction using seasonal ARIMA model with limited input data
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Optimal pavement design and rehabilitation planning using a mechanistic-empirical approach
inferredcites →https://doi.org/10.1016/j.econlet.2012.05.022openalex-snapshot
Flattening of the Phillips curve and the role of the oil price: An unobserved component model for the USA and Australia
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Neural network forecasting for seasonal and trend time series
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Unobserved Component models applied to the assessment of wear in railway points: A case study
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A hybrid macroscopic-based model for traffic flow in road networks
inferredcites →https://doi.org/10.1016/j.irfa.2004.10.004openalex-snapshot
An unobserved component model of asset pricing across financial markets
inferredcites →https://doi.org/10.1016/j.neucom.2015.12.013openalex-snapshot
A distributed spatial–temporal weighted model on MapReduce for short-term traffic flow forecasting
inferredcites →https://doi.org/10.1016/j.ress.2003.09.020openalex-snapshot
RCM2 predictive maintenance of railway systems based on unobserved components models
inferredcites →https://doi.org/10.1016/j.trb.2014.02.003openalex-snapshot
Joint optimization of freight facility location and pavement infrastructure rehabilitation under network traffic equilibrium
inferredcites →https://doi.org/10.1016/j.trb.2015.02.008openalex-snapshot
Nonlinear multivariate time–space threshold vector error correction model for short term traffic state prediction
inferredcites →https://doi.org/10.1016/j.trc.2005.04.007openalex-snapshot
Optimized and meta-optimized neural networks for short-term traffic flow prediction: A genetic approach
inferredcites →https://doi.org/10.1016/j.trc.2007.11.003openalex-snapshot
Adaptive hybrid fuzzy rule-based system approach for modeling and predicting urban traffic flow
inferredcites →https://doi.org/10.1016/j.trc.2013.11.011openalex-snapshot
A hybrid short-term traffic flow forecasting method based on spectral analysis and statistical volatility model
inferredcites →https://doi.org/10.1016/j.trc.2014.06.011openalex-snapshot
Traffic volume forecasting based on radial basis function neural network with the consideration of traffic flows at the adjacent intersections
inferredcites →https://doi.org/10.1016/j.trpro.2016.05.019openalex-snapshot
Short Term Traffic Prediction on the UK Motorway Network Using Neural Networks
inferredcites →https://doi.org/10.1016/s0169-2070(97)00044-7openalex-snapshot
Forecasting with artificial neural networks:
inferredcites →https://doi.org/10.1016/s0169-7439(03)00111-4openalex-snapshot
Using support vector machines for time series prediction
inferredcites →https://doi.org/10.1016/s0377-2217(00)00125-9openalex-snapshot
An object-oriented neural network approach to short-term traffic forecasting
inferredcites →https://doi.org/10.1017/cbo9781107049994openalex-snapshot
Forecasting, Structural Time Series Models and the Kalman Filter
inferredcites →https://doi.org/10.1061/(asce)0733-947x(2003)129:6(664)openalex-snapshot
Modeling and Forecasting Vehicular Traffic Flow as a Seasonal ARIMA Process: Theoretical Basis and Empirical Results
inferredcites →https://doi.org/10.1061/(asce)0733-947x(2004)130:4(452)openalex-snapshot
Optimizing Traffic Prediction Performance of Neural Networks under Various Topological, Input, and Traffic Condition Settings
inferredcites →https://doi.org/10.1061/(asce)0733-947x(2006)132:2(114)openalex-snapshot
Short-Term Freeway Traffic Flow Prediction: Bayesian Combined Neural Network Approach
inferredcites →https://doi.org/10.1061/(asce)0887-3801(2001)15:3(208)openalex-snapshot
Model Induction with Support Vector Machines: Introduction and Applications
inferredcites →https://doi.org/10.1061/(asce)te.1943-5436.0000435openalex-snapshot
Network-Scale Traffic Modeling and Forecasting with Graphical Lasso and Neural Networks
inferredcites →https://doi.org/10.1061/(asce)te.1943-5436.0000672openalex-snapshot
Improved k-nn for Short-Term Traffic Forecasting Using Temporal and Spatial Information
inferredcites →https://doi.org/10.1061/(asce)te.1943-5436.0000816openalex-snapshot
k-Nearest Neighbor Model for Multiple-Time-Step Prediction of Short-Term Traffic Condition
inferredcites →https://doi.org/10.1080/07350015.1993.10509962openalex-snapshot
Unobserved-Component Time Series Models With Markov-Switching Heteroscedasticity: Changes in Regime and the Link Between Inflation Rates and Inflation Uncertainty
inferredcites →https://doi.org/10.1080/10248070212011openalex-snapshot
Short-Term Traffic Flow Prediction Using Neuro-Genetic Algorithms
inferredcites →https://doi.org/10.1080/15472450600798551openalex-snapshot
A Wavelet Network Model for Short-Term Traffic Volume Forecasting
inferredcites →https://doi.org/10.1080/15732470500253164openalex-snapshot
Maintenance and management of civil infrastructure based on condition, safety, optimization, and life-cycle cost∗
inferredcites →https://doi.org/10.1088/1674-1056/18/6/014openalex-snapshot
Small-time scale network traffic prediction based on a local support vector machine regression model
inferredcites →https://doi.org/10.1093/oxfordhb/9780195398649.013.0006openalex-snapshot
Forecasting Economic Time Series Using Unobserved Components Time Series Models
inferredcites →https://doi.org/10.1109/bdcloud.2015.64openalex-snapshot
Predicting Spatiotemporal Traffic Flow Based on Support Vector Regression and Bayesian Classifier
inferredcites →https://doi.org/10.1109/iccis.2012.246openalex-snapshot
Research on K Nearest Neighbor Non-parametric Regression Algorithm Based on KD-Tree and Clustering Analysis
inferredcites →https://doi.org/10.1109/icmlc.2005.1527686openalex-snapshot
Elevator traffic flow prediction with least squares support vector machines
inferredcites →https://doi.org/10.1109/itsc.2008.4732609openalex-snapshot
Hybrid Process Neural Network based on Spatio-Temporal Similarities for Short-Term Traffic Flow Prediction
inferredcites →https://doi.org/10.1109/itsc.2010.5625123openalex-snapshot
Urban traffic network modeling and short-term traffic flow forecasting based on GSTARIMA model
inferredcites →https://doi.org/10.1109/mci.2009.932254openalex-snapshot
Time Series Prediction Using Support Vector Machines: A Survey
inferredcites →https://doi.org/10.1109/ssp.2011.5967651openalex-snapshot
Adaptive Bayesian network for traffic flow prediction
inferredcites →https://doi.org/10.1109/tits.2011.2174051openalex-snapshot
Neural-Network-Based Models for Short-Term Traffic Flow Forecasting Using a Hybrid Exponential Smoothing and Levenberg–Marquardt Algorithm
inferredcites →https://doi.org/10.1109/tits.2014.2345663openalex-snapshot
Traffic Flow Prediction With Big Data: A Deep Learning Approach
inferredcites →https://doi.org/10.1109/tits.2015.2453116openalex-snapshot
Time-Aware Multivariate Nearest Neighbor Regression Methods for Traffic Flow Prediction
inferredcites →https://doi.org/10.1109/tits.2015.2511156openalex-snapshot
Repeatability and Similarity of Freeway Traffic Flow and Long-Term Prediction Under Big Data
inferredcites →https://doi.org/10.1109/uksim.2014.67openalex-snapshot
Stock Price Prediction Using the ARIMA Model
inferredcites →https://doi.org/10.1111/j.1467-8667.2009.00606.xopenalex-snapshot
Optimal Long‐Term Infrastructure Maintenance Planning Accounting for Traffic Dynamics
inferredcites →https://doi.org/10.1139/cjce-2014-0447openalex-snapshot
Hybrid short-term freeway speed prediction methods based on periodic analysis
inferredcites →https://doi.org/10.1177/0361198106195700106openalex-snapshot
Matching Hourly, Daily, and Monthly Traffic Patterns to Estimate Missing Volume Data
inferredcites →https://doi.org/10.12720/ijsps.2.1.70-73openalex-snapshot
Short-Term Traffic Prediction Using Rainfall
inferredcites →https://doi.org/10.2139/ssrn.1496864openalex-snapshot
Structural Time Series Models and the Kalman Filter: A Concise Review
inferredcites →https://doi.org/10.2991/978-94-6239-102-4_2openalex-snapshot
Key Factors of K-Nearest Neighbours Nonparametric Regression in Short-Time Traffic Flow Forecasting
inferredcites →https://doi.org/10.3141/2215-09openalex-snapshot
Seasonal Autoregressive Integrated Moving Average and Support Vector Machine Models
inferredcites →https://doi.org/10.3846/16484142.2013.818057openalex-snapshot
SHORT TERM TRAFFIC FLOW PREDICTION IN HETEROGENEOUS CONDITION USING ARTIFICIAL NEURAL NETWORK
inferredcites →https://doi.org/10.4028/www.scientific.net/amr.532-533.1225openalex-snapshot
Paratactic Spatial-Temporal Two Dimension Data Fusion Based on Support Vector Machines for Traffic Flow Prediction of Abnormal State
inferredcites →https://doi.org/10.4304/jcp.8.10.2632-2639openalex-snapshot
K-SVM: An Effective SVM Algorithm Based on K-means Clustering
inferredcites →https://doi.org/10.5555/1756006.1859921openalex-snapshot
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation

What points at this work

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

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Forecasting Brazilian Railway Freight Volume: An Unobserved Components Model Application
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inferred← citeshttps://doi.org/10.1016/j.sciaf.2020.e00297openalex-snapshot
Unobserved component model with multi-interval input interventions: An application to crude oil production
inferred← citeshttps://doi.org/10.1061/jtepbs.teeng-7868openalex-snapshot
Lane-Level Short-Term Freeway Traffic Volume Prediction Based on Graph Convolutional Recurrent Network
inferred← citeshttps://doi.org/10.1080/23249935.2021.1948626openalex-snapshot
What can we learn from 9 years of ticketing data at a major transport hub? A structural time series decomposition
inferred← citeshttps://doi.org/10.1109/elmar49956.2020.9219023openalex-snapshot
Traffic Flow Forecasting at Micro-Locations in Urban Network using Bluetooth Detector
inferred← citeshttps://doi.org/10.1109/itsc55140.2022.9921809openalex-snapshot
Hybrid Spatio-Temporal Graph Convolution Network For Short-Term Traffic Forecasting
inferred← citeshttps://doi.org/10.1109/tits.2024.3447282openalex-snapshot
Deep Probabilistic Forecasting of Multivariate Count Data With “Sums and Shares” Distributions: A Case Study on Pedestrian Counts in a Multimodal Transport Hub
inferred← citeshttps://doi.org/10.1155/2023/9991872openalex-snapshot
Fitting Time Series Models to Fisheries Data to Ascertain Age
inferred← citeshttps://doi.org/10.14428/esann/2021.es2021-7openalex-snapshot
Machine learning and data mining for urban mobility intelligence
inferred← citeshttps://doi.org/10.3390/buildings15193467openalex-snapshot
Data Augmentation Using Multivariate Time Series Decomposition for Predicting Daily Energy Consumption of New Buildings
inferred← citeshttps://doi.org/10.3390/electronics11244146openalex-snapshot
Multivariate Demand Forecasting for Rental Bike Systems Based on an Unobserved Component Model
inferred← citeshttps://doi.org/10.3390/modelling2040026openalex-snapshot
Automated Machine Learning Pipeline for Traffic Count Prediction
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