基于改进视图聚类的装配式建筑构件识别方法  

Prefabricated Building Component Recognition Method Based on Improved View Clustering

作　　者：李志猛 廖伟文 洪学武 张龙 钟文 赵坚 LI Zhimeng;LIAO Weiwen;HONG Xuewu;ZHANG Long;ZHONG Wen;ZHAO Jian(School of Control and Mechanical Engineering,Tianjin Chengjian University,Tianjin 300384,China)

机构地区：[1]天津城建大学控制与机械工程学院,天津300384

出　　处：《河北工程大学学报（自然科学版）》2024年第5期8-15,共8页Journal of Hebei University of Engineering:Natural Science Edition

基　　金：天津市自然科学基金重点项目(16JCZDJC38600)。

摘　　要：为实现装配式建筑构件生产、存放和装配过程的智能化,设计了一种基于改进视图聚类的在线识别方法。该方法通过在信息瓶颈算法中加入标签信息嵌入和标签信息固化两个环节,将传统视图聚类算法改进为可用于装配式建筑构件在线识别的无监督模式识别方法。该方法在天津某工业化建筑公司的真实数据集上进行了测试,实验结果表明,模型识别精度达到90%以上,优于Softmax神经网络、支持向量机和贝叶斯网络等有监督模式识别方法。In order to realize the intelligence of the production,storage and assembly process of prefabricated building components,an online recognition method based on improved view clustering was designed.By adding label information embedding and label information solidification into the information bottleneck algorithm,the traditional view clustering algorithm was improved into an unsupervised pattern recognition method which could be used for online recognition of prefabricated building components.The method was tested on the real data set of an industrial construction company in Tianjin,and the experimental results show that the model recognition accuracy is above 90%,which is superior to Softmax neural network,support vector machine,Bayesian network and other supervised pattern recognition methods.

关 键 词：视图聚类 信息瓶颈 装配式 在线识别 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术] TU69[自动化与计算机技术—计算机科学与技术]