在城市科学中利用人工智能生成模型

Q3 Neuroscience
J Balsa-Barreiro, M Cebrián, M Menéndez, K Axhausen
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引用次数: 0

摘要

自 2000 年代末以来,城市已成为全球人类的主要栖息地,预计这一趋势在未来几十年将继续加强。随着我们越来越多地居住在人类设计的城市空间中,更好地理解这些环境如何影响人类行为以及个人如何看待城市变得至关重要。在本章中,我们将首先研究城市形态与社会行为之间的相互作用,强调城市形态的关键指标,并介绍最先进的数据收集方法。随后,我们利用最新一代人工智能(AI)基础模型的计算能力,在全球 21 座城市中模拟个人与城市建筑环境之间的互动。通过这一探索,我们仔细研究了这些模型在概括个人行为和感知城市的复杂性方面的能力。这些例子证明了先进的人工智能系统在帮助城市科学家理解城市方面的潜力,同时也强调了对其能力和局限性进行细致评估的必要性,以便在城市研究和政策制定中实现生成式人工智能的最佳应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leveraging Generative AI Models in Urban Science.

Since the late 2000s, cities have emerged as the primary human habitat across the globe, and this trend is anticipated to continue strengthening in the coming decades. As we increasingly inhabit human-designed urban spaces, it becomes crucial to understanding better how these environments influence human behavior and how individuals perceive the city. In this chapter, we begin by examining the interplay between urban form and social behavior, highlighting key indicators of urban morphology, and presenting state-of-the-art methodologies for data collection. Subsequently, we harness the computational capability of foundation models, the latest Artificial Intelligence (AI) generation, to simulate interactions between individuals and urban built environments in a diverse group of 21 cities across the globe. Through this exploration, we scrutinize the models' capacity to encapsulate the intricate complexities of how individuals behave and perceive cities. These examples demonstrate the potential of advanced AI systems to assist urban scientists in understanding cities, emphasizing the necessity for a meticulous evaluation of their capabilities and limitations for the optimal application of Generative AI in urban research and policymaking.

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来源期刊
Current topics in behavioral neurosciences
Current topics in behavioral neurosciences Neuroscience-Behavioral Neuroscience
CiteScore
4.80
自引率
0.00%
发文量
103
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