STAGE：用于轨迹生成的时空知识增强型多任务生成对抗网络（GAN）

IF 4.3 1区地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Geographical Information Science Pub Date : 2024-07-29 DOI:10.1080/13658816.2024.2381146

Zhongcai Cao, Kang Liu, Xin Jin, Li Ning, Ling Yin, Feng Lu

引用次数: 0

摘要

个人轨迹数据在城市规划、交通控制和流行病模拟等多个应用领域都发挥着举足轻重的作用。尽管目前的数据收集手段多种多样，但仍有一些技术无法满足需要。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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STAGE: a spatiotemporal-knowledge enhanced multi-task generative adversarial network (GAN) for trajectory generation

Individual trajectory data play a pivotal role in various application fields, such as urban planning, traffic control, and epidemic simulation. Despite the diverse means for data collection in curr...

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来源期刊

International Journal of Geographical Information Science 地学-计算机：信息系统

CiteScore

11.00

自引率

7.00%

发文量

审稿时长

9 months

期刊介绍： International Journal of Geographical Information Science provides a forum for the exchange of original ideas, approaches, methods and experiences in the rapidly growing field of geographical information science (GIScience). It is intended to interest those who research fundamental and computational issues of geographic information, as well as issues related to the design, implementation and use of geographical information for monitoring, prediction and decision making. Published research covers innovations in GIScience and novel applications of GIScience in natural resources, social systems and the built environment, as well as relevant developments in computer science, cartography, surveying, geography and engineering in both developed and developing countries.