随着城市化进程的加快，住房问题已经成为一个日益严峻的挑战。在土地资源有限的情况下，居民对住宅要求的提高和传统地产设计效率的低下难以匹配，因此提高住区规划方案设计效率成为了一个亟待解决的问题。传统的住区规划方案设计需要设计师具备丰富的经验和知识，而在城市化进程加速的情况下，设计师往往面临时间紧迫、任务繁重等压力，难以快速高效地完成住区规划设计。因此，利用人工智能技术提高住区规划方案设计效率成为了研究的重点。本研究利用人工智能平台和Rhino-Grasshopper平台，将传统的设计经验转化为筛选规则，实现了住区规划方案的自动化生成和评价。具体而言，本研究分为资料整理、方案生成实践、评价体系建立和智能设计深化四个阶段。首先，在资料整理阶段，收集了大量的住区规划方案设计资料，并以此为基础制定出规划方案筛选规则。利用人工智能平台翼排进行方案生成，在方案筛选实践阶段，利用Rhino-Grasshopper平台，将规划方案筛选规则转化为电池，实现了住区规划方案的自动化生成与筛选。最后，在智能设计深化阶段，借助人工智能工具便捷地生成符合人们的实际需求和使用情况的住区规划方案。通过以江苏省南京市的实际案例和具体的人工智能软件为切入点，本研究探讨了一种基于人工智能软件的住区规划方法，并通过对现有人工智能软件生成的住区规划方案结果进行分析评估，提高规划决策的科学性和可靠性。实验结果表明，该方法可以提高设计师的设计效率，并结合实践经验总结出借助人工智能软件的高效率和准确性帮助设计师更快速更准确地拟定住区规划方案。同时还可以帮助设计师更好地理解和评估规划方案的可行性和效果。本研究是应用人工智能技术提升住区规划方案设计效率的有益探索，对于未来的城市化进程和住房问题的解决具有一定的借鉴意义。
As the process of urbanization accelerates, the housing problem has become an increasingly serious challenge. The pressing need to enhance the effectiveness of residential area planning and design has arisen due to the limited land resources and the escalating demand for housing from inhabitants, which cannot be reconciled with the inadequate efficacy of conventional real estate design.Designers of traditional residential area planning and design must possess a wealth of experience and knowledge, yet in the face of accelerated urbanization, they often confront pressures such as tight deadlines and heavy workloads.The complexity of residential area planning and design renders it arduous to accomplish quickly and proficiently. Research has thus shifted its attention to the utilization of AI technology to enhance the productivity of residential area planning and design.In this study, artificial intelligence platform and Rhino-Grasshopper platform were used to transform traditional design experience into screening rules, and to achieve the automatic generation and evaluation of residential area planning schemes. Specifically, this study was divided into four stages: data collation, scheme generation practice, evaluation system establishment, and intelligent design deepening. Firstly, in the data collation stage, a large amount of residential area planning and design materials were collected, and based on this, planning scheme screening rules were formulated. Using the artificial intelligence platform YIPAI for scheme generation, in the scheme screening practice stage, the planning scheme screening rules were transformed into scripts using the Rhino-Grasshopper platform, achieving the automatic generation and screening of residential area planning schemes. Finally, in the intelligent design deepening stage, with the help of artificial intelligence tools, residential area planning schemes that meet people‘s actual needs and usage were conveniently generated.Through taking the actual case of Nanjing City, Jiangsu Province, and specific artificial intelligence software as the starting point, this study explores a residential area planning method based on artificial intelligence software, and through analyzing and evaluating the results of residential area planning schemes generated by existing artificial intelligence software, it improves the scientificity and reliability of planning decisions. The experimental results show that this method can improve the efficiency of designers‘ design and, by combining practical experience, summarize the use of artificial intelligence software to help designers more quickly and accurately formulate residential area planning schemes. It can also help designers better understand and evaluate the feasibility and effectiveness of planning schemes. Exploring the utilization of artificial intelligence technology to enhance the effectiveness of residential area planning and design is a highly advantageous endeavor.The future of urbanization and the resolution of housing issues are of particular importance.
