城市生态敏感区建筑群体高维空间规划建模分析

现有方法对城市生态敏感区建筑群体的规划研究较少，且规划效果较差，为此，提出一种城市生态敏感区建筑群体高维空间规划方法。采用矩形拟合优化方法对生态敏感区建筑群体图像进行处理，基于多尺度特征，对优化后的建筑群体图像进行分割。以分割后的图像为基础，将建筑群体数据转换为高维空间数据，建立建筑规划目标模型，并采用微粒群算法对目标模型进行求解，得到目标模型的全局最优值，完成对城市生态敏感区建筑群体高维空间的规划。实验结果表明，所提方法的建筑图像拟合误差最大不超过2.9%，拟合精度较高，且分割效果优于传统方法，目标模型最优值寻找耗时低于传统方法40%，规划效果评价结果良好。

Modeling and Analysis of High-dimensional Spatial Planning for Building groups in Urban Ecological sensitive areas

There are few researches on architectural population planning in urban ecologically sensitive areas, and the planning effect is poor. Therefore, a high-dimensional spatial planning method of architectural colony in urban ecologically sensitive areas is put forward. Based on the multi-scale feature, the optimized building group image is segmented by using rectangular fitting optimization method to process the architectural group image in the ecologically sensitive area. Based on the segmented image, the building group data is converted into high dimensional spatial data, the building planning target model is established, and the particle swarm optimization algorithm is used to solve the target model, and the global optimal value of the target model is obtained. To complete the high-dimensional space of the urban ecological sensitive area. Planning. The experimental results show that the building image fitting error of the proposed method is less than 2.9%, the fitting accuracy is high, and the segmentation effect is better than the traditional method, and the searching time of the optimal value of the target model is less than 40% of the traditional method. The result of planning effect evaluation is good.