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Lei Zhou, Weiye Xiao, Chen Wang, Haoran Wang
Pág. 143 - 161
Human mobility datasets, such as traffic flow data, reveal the connections between urban spaces. A novel framework is proposed to explore the spatial association between urban commercial and residential spaces via consumption travel flows in Shanghai. A ...
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Haiqiang Yang and Zihan Li
The objective imbalance between the taxi supply and demand exists in various areas of the city. Accurately predicting this imbalance helps taxi companies with dispatching, thereby increasing their profits and meeting the travel needs of residents. The ap...
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Jiusheng Du, Chengyang Meng and Xingwang Liu
This study utilizes taxi trajectory data to uncover urban residents? travel patterns, offering critical insights into the spatial and temporal dynamics of urban mobility. A fusion clustering algorithm is introduced, enhancing the clustering accuracy of t...
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Xiuxia Ma, Wenfa Peng, Bingwei Tong, Taiyun Li, Le Wang, Bin Du and Chaochao Li
To comprehensively comprehend the spatiotemporal variations in pollution load within the Sixth Drainage Ditch of the Ningxia Yellow River Diversion Irrigation Area, we employed the LOADEST model. We utilized daily flow data and concentrations of ammonia ...
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Ali Dorosti, Ali Asghar Alesheikh and Mohammad Sharif
Advancements in navigation and tracking technologies have resulted in a significant increase in movement data within road networks. Analyzing the trajectories of network-constrained moving objects makes a profound contribution to transportation and urban...
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Zhuangzhuang Yang, Chengxin Pang and Xinhua Zeng
Predicting the future trajectories of multiple agents is essential for various applications in real life, such as surveillance systems, autonomous driving, and social robots. The trajectory prediction task is influenced by many factors, including individ...
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Ruinan Chen, Jie Hu, Xinkai Zhong, Minchao Zhang and Linglei Zhu
Existing environment modeling approaches and trajectory planning approaches for intelligent vehicles are difficult to adapt to multiple scenarios, as scenarios are diverse and changeable, which may lead to potential risks. This work proposes a cognitive ...
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Liming Lao, Dangkui Du and Pengzhan Chen
This paper proposes a novel prediction model termed the social and spatial attentive generative adversarial network (SSA-GAN). The SSA-GAN framework utilizes a generative approach, where the generator employs social attention mechanisms to accurately mod...
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Jing Tian, Zilin Zhao and Zhiming Ding
With the widespread use of the location-based social networks (LBSNs), the next point-of-interest (POI) recommendation has become an essential service, which aims to understand the user?s check-in behavior at the current moment by analyzing and mining th...
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Sizhe Luo, Weiming Zeng and Bowen Sun
With the increasing popularity of automatic identification system AIS devices, mining latent vessel motion patterns from AIS data has become a hot topic in water transportation research. Trajectory similarity computation is a fundamental issue to many ma...
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