基于可视化特征提取的数字化城市BIM信息调度模型
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摘要
数字化城市BIM信息量巨大且处于不断变化中,传统调度模型在功能上处于高度耦合状态,降低了数字化城市BIM信息调度效率和访问速度,耗时长。因此,提出一种基于可视化特征提取的数字化城市BIM信息调度模型,将重心特征作为雷达图的可视化特征,通过原点到重心的距离对其进行提取。对覆盖体积、重叠体积与形状进行了综合分析,将三维柯西值作为评价因子,采用全局优化法进行最优节点选择,用于插入新目标。通过三维空间聚簇分组算法,引入k-均值算法,依据提取的可视化特征完成节点分裂操作,完成R树的大范围动态优化,实现了数字化城市BIM信息调度。实验结果表明,所提模型耗时短、能耗低、所占内存较少、BIM信息调度性能高,具有较好的实用性。
Digital city information plus the huge,in changing,the traditional scheduling model in highly coupled condition on the function,reduces the city BIM digital information scheduling efficiency and access speed,long time consuming. Therefore,put forward a kind of based on visual feature extraction of digital city information scheduling model,plus the focus features as radar map visualization,through the origin of the distance to the center of gravity. To cover the volume,the size and shape of comprehensive analysis of three dimensional cauchy value as evaluation factors,global optimization method is used to select the optimal node,is used to insert a new target. Through group 3D spatial clustering algorithm,k- means algorithm are introduced,based on visual characteristics of extraction of complete node split operation,complete R tree,a wide range of dynamic optimization,realized the digital urban BIM information scheduling. The experimental results show that the proposed model short time-consuming,low energy consumption,less memory,BIM information of scheduling performance is high,has a good practicability.
Digital city information plus the huge,in changing,the traditional scheduling model in highly coupled condition on the function,reduces the city BIM digital information scheduling efficiency and access speed,long time consuming. Therefore,put forward a kind of based on visual feature extraction of digital city information scheduling model,plus the focus features as radar map visualization,through the origin of the distance to the center of gravity. To cover the volume,the size and shape of comprehensive analysis of three dimensional cauchy value as evaluation factors,global optimization method is used to select the optimal node,is used to insert a new target. Through group 3D spatial clustering algorithm,k- means algorithm are introduced,based on visual characteristics of extraction of complete node split operation,complete R tree,a wide range of dynamic optimization,realized the digital urban BIM information scheduling. The experimental results show that the proposed model short time-consuming,low energy consumption,less memory,BIM information of scheduling performance is high,has a good practicability.
引文
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[2]林天扬,王佳,周小平.基于BIM的可视化消防管理平台研究[J].建筑科学,2015,31(6):152-155.
[3]王海豹,石宇良,张靖康,等.非关系数据库在物资调度系统中的应用模型研究[J].电子设计工程,2013,21(5):184-187.
[4]孔繁爽,伍艳莲,姜海燕.基于图像特征提取的生菜形态可视化建模[J].安徽农业科学,2015(24):265-268.
[5]梅健强,张军,贾凡,等.基于特征提取与跟踪的时变流体可视化系统的实现[J].天津职业技术师范大学学报,2015,25(2):1-6.
[6]曹国,高光林,丘衍航,等.基于World Wind平台的建筑信息模型在GIS中的应用[J].土木建筑工程信息技术,2013(5):114-117.
[7]郑娇,霍焱,曹殿才.3维GIS系统中海量3维模型合理调度的研究与实现[J].测绘与空间地理信息,2013,35(12):148-149.
[8]吴其煊,刘济(王禹),闫文凯.天津八大里项目数字城市UIM理念讨论[J].土木建筑工程信息技术,2013(4):103-109.
[9]辛佐先.城市轨道交通项目建筑信息模型(BIM)应用模式研究[J].城市轨道交通研究,2014,17(8):23-27.