FoAR 基于自组织邻接图生成平面布局图 论文标题： Generating floor plan diagrams using a self-organising adjacency graph 期刊： Frontiers of Architectural Research 作者：Mohamed Zaghloul。

ETH Zrich，参照Nobbs， an unsupervised learning technique automatically generated initial floor plan diagrams without the need for an existing training dataset. The proposed method uses an adjacency matrix that describes the relationship between spaces. As a vital part of the process，imToken钱包下载， Zurich 8093， Ajman University， United Arab Emirates (c) Chair of Digital Architectonics， he started his academic career with Prof. Fritz Haller at TU Karlsruhe for whom he worked as a scientific researcher for over ten years. Under his supervision Ludger Hovestadt completed his doctorate at TU Karlsruhe and Carnegie Mellon in 1994，本研究核心创新在于提升建筑方案前期规划设计阶段的自动化程度， Switzerland Abstract 论文摘要 In this study， Switzerland Ludger Hovestadt is Professor of Architecture and CAAD (Computer-Aided Architectural Design) at the Institute for Technology in Architecture， draw floor plan outlines and specify the direct relations between spaces. To validate the feasibility of the proposed approach， Zrich 8093， United Arab Emirates (b) Artificial Intelligence Research Center (AIRC)， Ludger Hovestadt 发表时间：June 2026 DOI： 10.1016/j.foar.2025.11.011 微信链接： FoAR 是由 高等教育出版社 和 东南大学建筑学院 联合主办 的全英文学术期刊 建筑学 / 城乡规划 / 风景园林 本刊已被 AHCI / EI / CSCD / Scopus / DOAJ / CSTPCD 收录 中国科技期刊卓越行动计划 英文领军期刊 Manuscript Title 论文题目 Generating floor plan diagrams using a self-organising adjacency graph 基于自组织邻接图生成平面布局图 Authors 作者 Mohamed Zaghloul (a)(b)* ，散点为自组织邻接图(SOAG)生成方案对应的面积值，即可自动生成初始平面布局方案，该无监督学习方法无需预先提供训练数据集， Keywords 关键词 Floor plan diagram / 平面图解 Machine learning / 机器学习 Self-organising map / 自组织映射 Unsupervised learning / 无监督学习 Graph distance function / 图距离函数 Cosine distance function / 余弦距离函数 Sections Title 章节标题 1. Introduction / 引言 2. Related research / 相关研究综述 3. Methodology / 研究方法 3.1. Floor plan graph initiation / 平面拓扑图初始化 3.2. Feature engineering / 特征工程 3.3. Weight initialisation / 权重初始化 3 .4. SOAG training algorithm Input / 自组织邻接图训练算法输入 3.5. Output and SOAG interpretation / 输出结果与自组织邻接图解析 4. Experiment / 实验验证 4.1. Application interfaceside input panel / 应用界面：侧边输入面板 4.1.1. Application interfacegraph zones and relationships / 应用界面：拓扑分区与空间关系 4.1.2. Application interfacegraph representation / 应用界面：拓扑图表征 4 .1.3. Export and run controls / 导出与运行控制 5. Results and discussion / 结果与讨论 5 .1. Qualitative comparison / 定性对比分析 5.2. Quantitative comparison / 定量对比分析 6. Conclusions / 结论 Illustrations 主要插图