MTSA-SC: A multi-task learning approach for individual trip destination prediction with multi-trajectory subsequence alignment and space-aware loss functions
Saved in:
| Main Authors: | Dan Luo, Fang Zhao, Hao Zhou, Chenxing Wang, Hao Xiong |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12143568/?tool=EBI |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
EL-MTSA: Stock Prediction Model Based on Ensemble Learning and Multimodal Time Series Analysis
by: Jianlei Kong, et al.
Published: (2025-04-01) -
Task-aware conditional GAN with multi-objective loss for realistic and efficient industrial time series generation
by: Kai Lang, et al.
Published: (2025-08-01) -
Energy-Aware Task Allocation for Multi-Cloud Networks
by: Sambit Kumar Mishra, et al.
Published: (2020-01-01) -
Destination-Aware Time-Constrained Task Allocation in Mobile Crowdsensing for Orienteering Application
by: Xia Hua, et al.
Published: (2025-01-01) -
Efficient Multi-Task Training with Adaptive Feature Alignment for Universal Image Segmentation
by: Yipeng Qu, et al.
Published: (2025-01-01)