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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...
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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...
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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...
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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...
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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 ...
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Zengyu Cai, Chunchen Tan, Jianwei Zhang, Liang Zhu and Yuan Feng
As network technology continues to develop, the popularity of various intelligent terminals has accelerated, leading to a rapid growth in the scale of wireless network traffic. This growth has resulted in significant pressure on resource consumption and ...
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Zijie Ding, Zhuoshi He, Zhihui Huang, Junfang Wang and Hang Yin
Accurate traffic flow prediction is highly important for relieving road congestion. Due to the intricate spatial?temporal dependence of traffic flows, especially the hidden dynamic correlations among road nodes, and the dynamic spatial?temporal character...
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Zijie Ding, Zhuoshi He, Zhihui Huang, Junfang Wang and Hang Yin
Accurate traffic flow prediction is highly important for relieving road congestion. Due to the intricate spatial?temporal dependence of traffic flows, especially the hidden dynamic correlations among road nodes, and the dynamic spatial?temporal character...
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Chunwei Hu, Xianfeng Liu, Sheng Wu, Fei Yu, Yongkun Song and Jin Zhang
Accurate crowd flow prediction is essential for traffic guidance and traffic control. However, the high nonlinearity, temporal complexity, and spatial complexity that crowd flow data have makes this problem challenging. This research proposes a dynamic g...
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Yumeng Wang, Ke Liu, Yuejun He, Pengfei Wang, Yuxin Chen, Hang Xue, Caiyi Huang and Lin Li
Forecasting air quality plays a crucial role in preventing and controlling air pollution. It is particularly significant for improving preparedness for heavily polluted weather conditions and ensuring the health and safety of the population. In this stud...
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Yumeng Wang, Ke Liu, Yuejun He, Pengfei Wang, Yuxin Chen, Hang Xue, Caiyi Huang and Lin Li
Forecasting air quality plays a crucial role in preventing and controlling air pollution. It is particularly significant for improving preparedness for heavily polluted weather conditions and ensuring the health and safety of the population. In this stud...
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Xiaoyuan Feng, Yue Chen, Hongbo Li, Tian Ma and Yilong Ren
Traffic flow prediction is an important function of intelligent transportation systems. Accurate prediction results facilitate traffic management to issue early congestion warnings so that drivers can avoid congested roads, thus directly reducing the ave...
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Xiliang Liu, Junjie Zhao, Shaofu Lin, Jianqiang Li, Shaohua Wang, Yumin Zhang, Yuyao Gao and Jinchuan Chai
Accurate and fine-grained individual air quality index (IAQI) prediction is the basis of air quality index (AQI), which is of great significance for air quality control and human health. Traditional approaches, such as time series, recurrent neural netwo...
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Yi Wang and Changfeng Jing
Benefiting from the rapid development of geospatial big data-related technologies, intelligent transportation systems (ITS) have become a part of people?s daily life. Traffic volume forecasting is one of the indispensable tasks in ITS. The spatiotemporal...
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Han Peng, Wengen Li, Chang Jin, Hanchen Yang and Jihong Guan
Sea Surface Temperature (SST) prediction is a hot topic that has received tremendous popularity in recent years. Existing methods for SST prediction usually select one sea area of interest and conduct SST prediction by learning the spatial and temporal d...
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Guoyan Xu, Yuwei Lu, Zixu Jing, Chunyan Wu and Qirui Zhang
The accuracy of dam deformation prediction is a key issue that needs to be addressed due to the many factors that influence dam deformation. In this paper, a dam deformation prediction model based on IEALL (IGWO-EEMD-ARIMA-LSTM-LSTM) is proposed for a si...
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Zhuhua Liao, Haokai Huang, Yijiang Zhao, Yizhi Liu and Guoqiang Zhang
Urban planning and function layout have important implications for the journeys of a large percentage of commuters, which often make up the majority of daily traffic in many cities. Therefore, the analysis and forecast of traffic flow among urban functio...
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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 ...
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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 ...
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