Bayesian Dynamic Linear Model with Adaptive Parameter Estimation for Short-Term Travel Speed Prediction
Bayesian dynamic linear model is a promising method for time series data analysis and short-term forecasting. One research issue concerns how the predictive model adapts to changes in the system, especially when shocks impact system behavior. In this study, we propose an adaptive dynamic linear mode...
Saved in:
| Main Authors: | Tai-Yu Ma, Yoann Pigné |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2019/5314520 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Bayesian Nonparametric Model for Estimating Multistate Travel Time Distribution
by: Emmanuel Kidando, et al.
Published: (2017-01-01) -
Piecewise Linear Labeling Method for Speed-Adaptability Enhancement in Human Gait Phase Estimation
by: Woolim Hong, et al.
Published: (2023-01-01) -
Bayesian and Non-Bayesian Estimation Methods for Simulating the Parameter of the Akshaya Distribution
by: Ahlam. H. Tolba
Published: (2022-11-01) -
Robust Short-Term Wind Speed Forecasting Using Adaptive Shallow Neural Networks
by: Matrenin P.V., et al.
Published: (2020-09-01) -
A New Approach to Estimate Real-Time Traveling Speed with Accelerometer
by: Xiaojie Zong, et al.
Published: (2015-10-01)