摘要
面对实景三维服务空间规划的快速决策需求,传统的规划决策模型较难实现规则联动和动态视觉相结合的模型制定,利用知识图谱实现多源数据的语义关联,定量化解析国土空间规划要素及其关系,构建了服务规划决策的智能组合语义搜索框架,提升复杂规划需求场景下决策推荐的准确性、专业性和可解释性。通过制定地块评价规则和参数优化规则,构建规划决策规则库,形成“规则-优化-自适应”模式的规划地块选址推荐和规划方案设计参数优化的综合决策。模型为江苏省某市国土空间规划决策提供可视化决策支持,准确率高达95%,决策效率提升80%。
Facing the rapid decision-making needs of spatial planning supported by 3D real-scene services,traditional planning decision-making models struggle to formulate models that combine rule linkage with dynamic visualization.By using knowledge graphs to achieve semantic association of multi-source data,quantitatively analyzing elements and their relationships in territorial spatial planning,an intelligent composite semantic search framework serving planning decision-making has been constructed.This framework enhances the accuracy,professionalism,and interpretability of decision recommendations in scenarios with complex planning needs.Through formulating plot evaluation rules and parameter optimization rules,a planning decision-making rule database has been built,forming comprehensive decision-making for planning plot site selection recommendation and planning scheme design parameter optimization under the“rule-optimization-adaptation”model.The model provides visual decision support for territorial spatial planning decision-making in a city in Jiangsu Province,with an accuracy rate as high as 95%and an 80%improvement in decision-making efficiency.
作者
徐慧珺
XU Huijun(Provincial Geomatic Center of Jiangsu,Nanjing 210013,China)
出处
《江苏科技信息》
2025年第21期126-132,共7页
Jiangsu Science and Technology Information
关键词
规划决策
实景三维
知识图谱
语义关联
规则库
参数优化
planning decision-making
3D real-scene
knowledge graphs
semantic association
rule database
parameter optimization
