人工智能在施工管理中的潜力

W. Eber
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引用次数: 19

摘要

摘要自20世纪50年代信息技术问世以来,人工智能方法得到了发展。随着计算能力的提高,新的强大算法,特别是互联网作为一种巨大的非结构化数据资源的可用性,为人工智能有用性的讨论注入了活力。这尤其给建筑管理带来了希望,因为建筑项目最近变得越来越大、越来越复杂,也就是说,在给定的时间和预算越来越紧的情况下,越来越多的参与者关注不同的利益。最后,施工管理用于建立所有这些问题的有效组织,并能够高度准确和确定地预测结果。当项目规模较小时,这可以由人类的思维来实现,但随着最近的发展,人类的思维显然被推向了极限。在这种背景下,在开发工具之前,需要从理论层面研究人工智能对组织任务的可能支持。本文是《建筑管理中的人工智能——一个视角》一文的扩展版,该文在2019年创意建筑大会上发表,在该会议上,人工智能的算法和熵范围在建筑管理的背景下进行了研究。然而,高效的组织是将系统重组为一组分离良好的子系统,在这些子系统中,人类智能主要需要引入人工智能无法提供的两个更高的原则:优先排序的能力和允许非从给定数据得出的新方法的创造力。本文还重点讨论了原位配合方面。该服务是组织的一个不可分离的方面,因此只能被视为位于层级控制之外的自主子系统。在这一点上,人工智能的算法需要研究,与其说是为了取代人类的思维,不如说是为了提供重要的支持。
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Potentials of artificial intelligence in construction management
Abstract Artificial intelligence (AI) approaches have been developed since the upcoming of Information Technologies beginning in the 1950s. With rising computing power, the discussion of AI usefulness has been refuelled by new powerful algorithms and, in particular, the availability of the internet as a vast resource of unstructured data. This gives hope to construction management in particular, since construction projects are recently becoming larger and more complex, i.e. encompassing more and more participants focusing on diverging interests while the given frames of time and budget are getting tighter. Finally, construction management is used to establish an efficient organisation of all these issues and able to predict the result with a high degree of precision and certainty. This could be accomplished by the human mind when projects were smaller, but with the recent development human mind is clearly pushed to its limits. On this background, the possible support of AI to organisational tasks needs to be investigated on a theoretical level prior to developing tools. This paper is the extended version of the article ‘Artificial Intelligence in Construction Management – a Perspective’, presented at the Creative Construction Conference 2019 where the algorithmic and entropic scope of AI is investigated in the context of construction management. However, efficient organisation is about restructuring systems into a set of well-separated subsystems, where human intelligence is required to bring in mainly two higher principles which AI fails to provide: the ability to prioritise and creativity allowing for new approaches not derived from given data. This paper additionally focuses on the aspect of in-situ coordination. This service is an aspect of organisation which is not separable and can therefore only be treated as self-determined subsystem, located outside of hierarchical control. At this point algorithms of AI need to be investigated not so much as to substitute human mind but to provide significant support.
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来源期刊
CiteScore
3.10
自引率
0.00%
发文量
8
审稿时长
16 weeks
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