Titlebook: Enabling Smart Urban Services with GPS Trajectory Data; Chao Chen,Daqing Zhang,Hongyu Huang Book 2021 The Editor(s) (if applicable) and Th

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ScenicPlanner: Recommending the Most Beautiful Driving Routes Area in the city of San Francisco, CA, USA. Results show that it obtains high-quality solutions that are reasonably close to the optima but within desirable computation time and considerably better than the baseline solutions of genetic algorithms.

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Clinical Utility (Applications) of SPECT/CTlications in a smart city by using these mobile devices. Intuitively, uploading true locations to the server will improve the quality of services. But this also brings leakage of our location privacy. Even if locations are perturbed before submission, the correlation between successive locations ena

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https://doi.org/10.1007/978-1-4842-0097-1e skills to . for low-performance taxi drivers. Thanks to the widely available large-scale taxi GPS trajectory data, service strategies of taxi drivers that are hidden in their trajectory data can be uncovered by data mining techniques. In this chapter, we investigate taxi service strategies from th

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https://doi.org/10.1007/978-1-4842-3036-7lized fuel consumption model (PFCM) for each driver, based on the individual driving behaviors embedded in the GPS trajectory data and the physical features (e.g., traffic lights, stop signs, road network topology) along the routes provided by road network data. Furthermore, we build a general PFCM

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