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城市低碳群体建筑外部边缘空间规划仿真研究
引用本文:董艳林,刘懿韬.城市低碳群体建筑外部边缘空间规划仿真研究[J].计算机仿真,2020,37(4):215-218,249.
作者姓名:董艳林  刘懿韬
作者单位:东北电力大学建筑工程学院,吉林长春132000;华南农业大学水利与土木工程学院,广东广州510642
摘    要:针对当前空间规划方法存在的计算时间长、规划成本高等问题,提出一种基于蚁群算法的低碳群体建筑外部边缘空间规划方法。依据城市低碳群体建筑外部边缘空间的模糊特性,引入模糊集合理论对建筑外部边缘空间进行理解和建筑外部边缘空间模糊矩阵的构建,对边缘空间进行划分和限定。结合建筑外部边缘空间的特性和具体关系模式进行空间层次划分,计算空间属性权重,以此确立空间规划目标,根据空间规划目标函数构建空间规划模型,设定求解空间规划模型的蚁群算法信息素更新方式,依据个体信息素转移概率指导个体进行模型最优解搜索。实验结果表明,所提方法与传统的空间规划方法相比,有效减少了计算时间,降低了规划成本。

关 键 词:城市低碳群体  建筑外部边缘  空间规划  蚁群算法

Simulation Research on Exterior Edge Space Planning of Urban Low Carbon Group Buildings
DONG Yan-lin,LIU Yi-tao.Simulation Research on Exterior Edge Space Planning of Urban Low Carbon Group Buildings[J].Computer Simulation,2020,37(4):215-218,249.
Authors:DONG Yan-lin  LIU Yi-tao
Affiliation:(School of Civil Engineering and Architecture,Northeast Electric Power University,Changchun Jilin 132000,China;College of Water Conservancy and Civil Engineering,SCAU,Guangzhou Guangdong 510642,China)
Abstract:In this paper, a method to plan external edge space of building for low-carbon group based on ant colony algorithm was proposed. According to the fuzzy characteristics of the outer edge space of building for urban low-carbon group, the theory of fuzzy set was introduced to understand the outer edge space of building and construct the fuzzy matrix of outer edge space of building. And then, the edge space was divided and restricted. Based on the characteristics of outer edge space of the building and the specific relationship pattern, the spatial hierarchical division was carried out and the spatial attribute weights were calculated, so that the spatial planning objective was determined. According to the spatial planning objective function, the spatial planning model was constructed. Finally, the pheromone updating mode of ant colony algorithm to solve the spatial planning model was set. According to the individual pheromone transfer probability, we could guide the individual to perform the optimal solution search. Simulation results show that the proposed method can effectively reduce the calculation time and the planning cost.
Keywords:Urban low-carbon group  Outer edge of building  Spatial planning  Ant colony algorithm
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