Zobrazeno 1 - 10
of 129
pro vyhledávání: '"Hou, Zhuoran"'
A number of methods have been proposed for causal effect estimation, yet few have demonstrated efficacy in handling data with complex structures, such as images. To fill this gap, we propose Causal Multi-task Deep Ensemble (CMDE), a novel framework t
Externí odkaz:
http://arxiv.org/abs/2301.11351
Autor:
Hu, Jincheng, Lin, Yang, Li, Jihao, Hou, Zhuoran, Zhao, Dezong, Zhou, Quan, Jiang, Jingjing, Zhang, Yuanjian
Reinforcement learning-based (RL-based) energy management strategy (EMS) is considered a promising solution for the energy management of electric vehicles with multiple power sources. It has been shown to outperform conventional methods in energy man
Externí odkaz:
http://arxiv.org/abs/2212.09154
The problem of robustness in adverse weather conditions is considered a significant challenge for computer vision algorithms in the applicants of autonomous driving. Image rain removal algorithms are a general solution to this problem. They find a de
Externí odkaz:
http://arxiv.org/abs/2211.09959
Autor:
Hu, Jincheng, Lin, Yang, Chu, Liang, Hou, Zhuoran, Li, Jihan, Jiang, Jingjing, Zhang, Yuanjian
The high emission and low energy efficiency caused by internal combustion engines (ICE) have become unacceptable under environmental regulations and the energy crisis. As a promising alternative solution, multi-power source electric vehicles (MPS-EVs
Externí odkaz:
http://arxiv.org/abs/2211.04001
The multi-source electromechanical coupling makes the energy management of fuel cell electric vehicles (FCEVs) relatively nonlinear and complex especially in the types of 4-wheel-drive (4WD) FCEVs. Accurate state observing for complicated nonlinear s
Externí odkaz:
http://arxiv.org/abs/2209.04995
Accurate traffic conditions prediction provides a solid foundation for vehicle-environment coordination and traffic control tasks. Because of the complexity of road network data in spatial distribution and the diversity of deep learning methods, it b
Externí odkaz:
http://arxiv.org/abs/2209.03629
In recent years, significant progress has been made in transportation electrification. And lithium-ion batteries (LIB), as the main energy storage devices, have received widespread attention. Accurately predicting the state of health (SOH) can not on
Externí odkaz:
http://arxiv.org/abs/2209.05253
Spatial-Temporal Feature Extraction and Evaluation Network for Citywide Traffic Condition Prediction
Traffic prediction plays an important role in the realization of traffic control and scheduling tasks in intelligent transportation systems. With the diversification of data sources, reasonably using rich traffic data to model the complex spatial-tem
Externí odkaz:
http://arxiv.org/abs/2207.11034
Traffic speed prediction is the key to many valuable applications, and it is also a challenging task because of its various influencing factors. Recent work attempts to obtain more information through various hybrid models, thereby improving the pred
Externí odkaz:
http://arxiv.org/abs/2207.11030
Autor:
Zhao, Di, Chu, Liang, Hou, Zhuoran, Zhou, Quan, Liu, Yonggang, Huang, Yanjun, Chen, Zheng, Zhao, Dezong, Zhang, Yuanjian
Publikováno v:
In Energy 30 November 2024 310
