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Jiahui Zhao, Zhibin Li, Pan Liu, Mingye Zhang
Pág. 115 - 142
Demand prediction plays a critical role in traffic research. The key challenge of traffic demand prediction lies in modeling the complex spatial dependencies and temporal dynamics. However, there is no mature and widely accepted concept to support the so...
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Gulshan Saleem, Usama Ijaz Bajwa, Rana Hammad Raza and Fan Zhang
Surveillance video analytics encounters unprecedented challenges in 5G and IoT environments, including complex intra-class variations, short-term and long-term temporal dynamics, and variable video quality. This study introduces Edge-Enhanced TempoFuseNe...
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Antoine Soloy, Carlos Lopez Solano, Emma Imen Turki, Ernesto Tonatiuh Mendoza and Nicolas Lecoq
This study delves into the morphodynamic changes of pebble beaches in response to storm events, employing a combination of observational and numerical approaches. This research focuses on three extreme events, meticulously examining morhological changes ...
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Tianyu Dong, Jiazu Zhou, Junfan Zhuo, Bo Li and Feng Zhu
Conventional traffic stability studies primarily concentrate on the evolution of disturbances in vehicle motion but seldom consider how collision risk changes spatially and temporally. This study bridges the gap by extending the principles of traffic sta...
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Amalia Nafisah Rahmani Irawan and Daisuke Komori
There is valuable information that can be obtained beyond using a fixed crop calendar with coarse spatial resolution. Knowing the dynamics of the timing and location in which a particular crop is planted and harvested, with an annual temporal resolution ...
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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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Yuhao He, Qianlong Zhao, Shanqi Sun, Wenjing Li and Waishan Qiu
The COVID-19 outbreak followed by the strict citywide lockdown in Shanghai has sparked negative emotion surges on social media platforms in 2022. This research aims to investigate the spatial?temporal heterogeneity of a unique emotion (helplessness) and ...
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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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Jingtao Sun, Jin Qi, Zhen Yan, Yadong Li, Jie Liang and Sensen Wu
The COVID-19 pandemic has had a profound impact on people?s lives, making accurate prediction of epidemic trends a central focus in COVID-19 research. This study innovatively utilizes a spatiotemporal heterogeneity analysis (GTNNWR) model to predict COVI...
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Siyuan Chen, Zao Zhang, Cheng Wang, Lifeng Tan, Huanjie Liu, Hong Yuan, Rui Zhang and Rui Hu
Photovoltaic (PV) power generation is emerging as a key aspect of the global shift towards a more sustainable energy mix. Nevertheless, existing assessment models predominantly concentrate on predicting the overall capacity of PV power generation, often ...
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