[HTML][HTML] Making data classification more effective: An automated deep forest model
Despite a small overfitting risk, the deep forest model and its variants cannot automatically
match data features; they rely on manual experience and comparative experiments for forest …
match data features; they rely on manual experience and comparative experiments for forest …
[HTML][HTML] Travel time prediction for an intelligent transportation system based on a data-driven feature selection method considering temporal correlation
Travel-time prediction is a critical component of Intelligent Transportation Systems (ITS),
offering vital information for tasks such as accident detection, congestion management, and …
offering vital information for tasks such as accident detection, congestion management, and …
Enhancing train travel time prediction for China–Europe railway express: A transfer learning-based fusion technique
Accurate train travel time (Tt) is crucial for the quality and reliability of rail transport services,
particularly for China–Europe Railway Express (CRE), which occupies an important position …
particularly for China–Europe Railway Express (CRE), which occupies an important position …
Filter transfer learning algorithm for nonlinear systems modeling with heterogeneous features
H Han, M Li, X Wu, H Yang, J Qiao - Expert Systems with Applications, 2025 - Elsevier
Transfer learning can handle the domain adaptation of different feature spaces in nonlinear
systems. Most existing studies only focus on common features between heterogeneous …
systems. Most existing studies only focus on common features between heterogeneous …
[HTML][HTML] BAT-Transformer: Prediction of Bus Arrival Time with Transformer Encoder for Smart Public Transportation System
S Jeong, C Oh, J Jeong - Applied Sciences, 2024 - mdpi.com
In urban public transportation systems, the accuracy of bus arrival time prediction is crucial
to reduce passenger waiting time, increase satisfaction, and ensure efficient transportation …
to reduce passenger waiting time, increase satisfaction, and ensure efficient transportation …
A Novel Hybrid Deep Learning Model for Complex Systems: A Case of Train Delay Prediction
D Wang, J Guo, C Zhang - Advances in Civil Engineering, 2024 - Wiley Online Library
Predicting the status of train delays, a complex and dynamic problem, is crucial for railway
enterprises and passengers. This paper proposes a novel hybrid deep learning model …
enterprises and passengers. This paper proposes a novel hybrid deep learning model …
Hybrid deep learning model for vegetable price forecasting based on principal component analysis and attention mechanism
X Chen, C Cai, X He, D Mei - Physica Scripta, 2024 - iopscience.iop.org
With the aim of enhancing the accuracy of current models for forecasting vegetable prices
and improving market structures, this study focuses on the prices of bell peppers at the …
and improving market structures, this study focuses on the prices of bell peppers at the …
[PDF][PDF] Journal of Industrial Information Integration
Despite a small overfitting risk, the deep forest model and its variants cannot automatically
match data features; they rely on manual experience and comparative experiments for forest …
match data features; they rely on manual experience and comparative experiments for forest …
[PDF][PDF] Transportation Engineering
Travel-time prediction is a critical component of Intelligent Transportation Systems (ITS),
offering vital information for tasks such as accident detection, congestion management, and …
offering vital information for tasks such as accident detection, congestion management, and …