|
|
|
|
|
Zhengyan Cui, Junjun Zhang, Giseop Noh and Hyun Jun Park
Traffic prediction is a popular research topic in the field of Intelligent Transportation System (ITS), as it can allocate resources more reasonably, relieve traffic congestion, and improve road traffic efficiency. Graph neural networks are widely used i...
ver más
|
|
|
|
|
|
|
|
|
|
|
Miaomiao Hou, Xiaofeng Hu, Jitao Cai, Xinge Han and Shuaiqi Yuan
Crime issues have been attracting widespread attention from citizens and managers of cities due to their unexpected and massive consequences. As an effective technique to prevent and control urban crimes, the data-driven spatial?temporal crime prediction...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ping Huang and Yafeng Wu
Airborne speech enhancement is always a major challenge for the security of airborne systems. Recently, multi-objective learning technology has become one of the mainstream methods of monaural speech enhancement. In this paper, we propose a novel multi-o...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhihong Chang, Chunsheng Liu and Jianmin Jia
As an important component of intelligent transportation-management systems, accurate traffic-parameter prediction can help traffic-management departments to conduct effective traffic management. Due to the nonlinearity, complexity, and dynamism of highwa...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zeying Bian, Mengyuan Zeng, Hongduo Zhao, Mu Guo and Juewei Cai
Measuring the axle loads of vehicles with more accuracy is a crucial step in weight enforcement and pavement condition assessment. This paper proposed a vibration-based method, which has an extended sensing range, high temporal sampling rate, and dense s...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xiaofeng Liu, Liuqi Xiong, Yiming Zhang and Chenshuang Luo
Turbofan engines are known as the heart of the aircraft. The turbofan?s health state determines the aircraft?s operational status. Therefore, the equipment monitoring and maintenance of the engine is an important part of ensuring the healthy and stable o...
ver más
|
|
|
|
|
|
|
|
|
|
|
Meng Wu and Pudong Shi
To address the problem of poor detection and under-utilization of the spatial relationship between nodes in human pose estimation, a method based on an improved spatial temporal graph convolutional network (ST-GCN) model is proposed. Firstly, upsampling ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ke Shang, Zeyu Wan, Yulin Zhang, Zhiwei Cui, Zihan Zhang, Chenchen Jiang and Feizhou Zhang
The accurate and rapid prediction of parking availability is helpful for improving parking efficiency and to optimize traffic systems. However, previous studies have suffered from limited training sample sizes and a lack of thorough investigation into th...
ver más
|
|
|
|
|
|
|
|
|
|
|
Wei Li, Xi Zhan, Xin Liu, Lei Zhang, Yu Pan and Zhisong Pan
Traffic prediction plays a significant part in creating intelligent cities such as traffic management, urban computing, and public safety. Nevertheless, the complex spatio-temporal linkages and dynamically shifting patterns make it somewhat challenging. ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chin-Yi Chen and Jih-Jeng Huang
Traditional movie recommendation systems are increasingly falling short in the contemporary landscape of abundant information and evolving user behaviors. This study introduced the temporal knowledge graph recommender system (TKGRS), a ground-breaking al...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yinglin Wang and Xinyu Xu
Reasoning on temporal knowledge graphs, which aims to infer new facts from existing knowledge, has attracted extensive attention and in-depth research recently. One of the important tasks of reasoning on temporal knowledge graphs is entity prediction, wh...
ver más
|
|
|
|
|
|
|
|
|
|
|
Aling Luo, Boyi Shangguan, Can Yang, Fan Gao, Zhe Fang and Dayu Yu
Taxi demand forecasting plays an important role in ride-hailing services. Accurate taxi demand forecasting can assist taxi companies in pre-allocating taxis, improving vehicle utilization, reducing waiting time, and alleviating traffic congestion. It is ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Junwei Zhou, Xizhong Qin, Kun Yu, Zhenhong Jia and Yan Du
Accurate urban traffic flow prediction plays a vital role in Intelligent Transportation System (ITS). The complex long-term and long-range spatiotemporal correlations of traffic flow pose a significant challenge to the prediction task. Most current resea...
ver más
|
|
|
|
|
|
|
|
|
|
|
Qiongfang Yu, Liang Zhao and Yi Yang
For low-voltage three-phase systems, the deep fault arc features are difficult to extract, and the phase information has strong timing. This phenomenon leads to the problem of low accuracy of fault phase selection. This paper proposes a three-phase fault...
ver más
|
|
|
|
|
|
|
|
|
|
|
Indra Riyanto, Mia Rizkinia, Rahmat Arief and Dodi Sudiana
Flooding in urban areas is counted as a significant disaster that must be correctly mitigated due to the huge amount of affected people, material losses, hampered economic activity, and flood-related diseases. One of the technologies available for disast...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chao Chen, Weiyu Guo, Chenfei Ma, Yongkui Yang, Zheng Wang and Chuang Lin
Since continuous motion control can provide a more natural, fast and accurate man?machine interface than that of discrete motion control, it has been widely used in human?robot cooperation (HRC). Among various biological signals, the surface electromyogr...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jing Li, Wenyue Guo, Haiyan Liu, Xin Chen, Anzhu Yu and Jia Li
Predicting user activity intensity is crucial for various applications. However, existing studies have two main problems. First, as user activity intensity is nonstationary and nonlinear, traditional methods can hardly fit the nonlinear spatio-temporal r...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiandong Bai, Jiawei Zhu, Yujiao Song, Ling Zhao, Zhixiang Hou, Ronghua Du and Haifeng Li
Accurate real-time traffic forecasting is a core technological problem against the implementation of the intelligent transportation system. However, it remains challenging considering the complex spatial and temporal dependencies among traffic flows. In ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kewei Ouyang, Yi Hou, Shilin Zhou and Ye Zhang
Recently, some researchers adopted the convolutional neural network (CNN) for time series classification (TSC) and have achieved better performance than most hand-crafted methods in the University of California, Riverside (UCR) archive. The secret to the...
ver más
|
|
|
|
|
|
|
|
|
|
|
Liang Ge, Siyu Li, Yaqian Wang, Feng Chang and Kunyan Wu
Traffic speed prediction plays a significant role in the intelligent traffic system (ITS). However, due to the complex spatial-temporal correlations of traffic data, it is very challenging to predict traffic speed timely and accurately. The traffic speed...
ver más
|
|
|
|
|
|