An Improved Selective Ensemble Learning Method for Highway Traffic Flow State Identification
Reliable and accurate real-time traffic flow state identification is crucial for an intelligent transportation system (ITS). This identification is a prerequisite for alleviating traffic congestion and improving highway operation efficiency. In this paper, we propose an improved traffic flow state i...
Guardado en:
Autores principales: | Zhanzhong Wang, Ruijuan Chu, Minghang Zhang, Xiaochao Wang, Siliang Luan |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
IEEE
2020
|
Materias: | |
Acceso en línea: | https://doaj.org/article/c0b35f36b65f42f68d982cfc4b93a26e |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Random Subspace Ensembles of Fully Convolutional Network for Time Series Classification
por: Yangqianhui Zhang, et al.
Publicado: (2021) -
Deep Spatial-Spectral Subspace Clustering for Hyperspectral Images Based on Contrastive Learning
por: Xiang Hu, et al.
Publicado: (2021) -
Comparision of performance of multi criteria decision making ensemble-clustering algorithms in rainfall frequency analysis
por: Nilotpal Debbarma, et al.
Publicado: (2021) -
Fuzzy Integral-Based Multi-Classifiers Ensemble for Android Malware Classification
por: Altyeb Taha, et al.
Publicado: (2021) -
A Combined Strategy of Improved Variable Selection and Ensemble Algorithm to Map the Growing Stem Volume of Planted Coniferous Forest
por: Xiaodong Xu, et al.
Publicado: (2021)