基于机器学习的人工智能辅助规划前景展望
发布时间：2018-11-03 07:01
【摘要】：城乡规划行业的设计生产周期产生了大量的非结构化数据,传统信息技术仅实现了对规划成果信息的档案式存储,随着人工智能技术的重要分支——机器学习技术的迅猛发展,对规划全流程知识挖掘辅助提高规划编制科学性和效率成为了可能。通过跨学科文献调研和示范案例实验,展示了规划支持模型智能化和规划文本知识挖掘两方面的技术演进路径。最后,展望了规划编制全过程的人工智能辅助技术总体趋势。
[Abstract]:The design and production cycle of urban and rural planning industry has produced a large amount of unstructured data. Traditional information technology has only realized the archival storage of planning achievement information. With the rapid development of machine learning technology, which is an important branch of artificial intelligence technology, It is possible to improve the scientificalness and efficiency of planning compilation with the aid of knowledge mining in the whole process of planning. Based on cross-disciplinary literature research and demonstration case experiments, the technological evolution paths of intelligent planning support model and planning text knowledge mining are demonstrated. Finally, the general trend of artificial intelligence auxiliary technology in the whole process of programming is prospected.
【作者单位】： 广东省住房和城乡建设厅政策研究中心;广东省城乡规划设计研究院;
【分类号】：TP18;TU981
本文编号：2307047
[Abstract]:The design and production cycle of urban and rural planning industry has produced a large amount of unstructured data. Traditional information technology has only realized the archival storage of planning achievement information. With the rapid development of machine learning technology, which is an important branch of artificial intelligence technology, It is possible to improve the scientificalness and efficiency of planning compilation with the aid of knowledge mining in the whole process of planning. Based on cross-disciplinary literature research and demonstration case experiments, the technological evolution paths of intelligent planning support model and planning text knowledge mining are demonstrated. Finally, the general trend of artificial intelligence auxiliary technology in the whole process of programming is prospected.
【作者单位】： 广东省住房和城乡建设厅政策研究中心;广东省城乡规划设计研究院;
【分类号】：TP18;TU981
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