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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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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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Chao Jiang, Lin Liu, Xiaoxing Qin, Suhong Zhou and Kai Liu
The importance of combining spatial and temporal aspects has been increasingly recognized over recent years, yet pertinent pattern analysis methods in place-based crime research still need further development to explicitly indicate spatial-temporal local...
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Susan M. Kotikot and Olufemi A. Omitaomu
Major droughts in the United States have heavily impacted the hydrologic system, negatively effecting energy and food production. Improved understanding of historical drought is critical for accurate forecasts. Data from global climate models (GCMs), com...
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Di Wang, Tomio Miwa and Takayuki Morikawa
The paradigms of taxis and ride-hailing, the two major players in the personal mobility market, are compared systematically and empirically in a unified spatial?temporal context. Supported by real field data from Xiamen, China, this research proposes a t...
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