文章摘要
唐芃,李鸿渐,王笑,[德]卢德格尔·霍夫施塔特.基于机器学习的传统建筑聚落历史风貌保护生成设计方法——以罗马Termini 火车站周边地块城市更新设计为例[J].建筑师,2019,(1):100-105.
基于机器学习的传统建筑聚落历史风貌保护生成设计方法——以罗马Termini 火车站周边地块城市更新设计为例
Generative Design on Conservation and Inheritance of Traditional Architecture and Settlement Based on Machine Learning: A Case Study on the Urban Renewal Design of Roma Termini Railway Station
  
DOI:
中文关键词: 传统建筑聚落、机器学习、生成设计、基于案例推理
英文关键词: Traditional Architecture and Settlement, Machine Learning, Generative Design, Case-based Reasoning
基金项目:
作者单位
唐芃  
李鸿渐  
王笑  
[德]卢德格尔·霍夫施塔特  
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中文摘要:
      本文关注在传统建筑聚落的历史风貌保护或更新设计中,如何依靠计算机信息技术获得不依赖于人的主观判断 的传统空间形态构成规则,建立数字化生成设计工具,来解答传统建筑聚落历史文化信息的精确传承和创新利用的 问题。文中介绍了人工智能领域中的数据挖掘和机器学习对以上问题的解决可能,并结合案例介绍了 “基于案例学习” 等技术工具在城市历史地段城市更新设计中的应用成果。探索了基于知识发现的生成设计工具对传统建筑聚落历史 风貌保护所起到的作用。
英文摘要:
      This paper focused on how to obtain the traditional rules of spatial form that do not rely on human subjective judgments in the conservation planning of traditional architecture and settlement, how to establish the generative design method based on digital technology, and thus to complete the accurate inheritance and innovative use of historical and cultural information. It introduced the possibility of dealing with such problems by data mining and machine learning in the fi eld of artifi cial intelligence. A case was introduced to show the achievements by using Case-based Learning in darning space texture of urban historical area in the urban renewal design. All the studies explored the role of knowledge discovery on generative design in the conservation planning of traditional architecture and settlement.
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