检索结果-内蒙古大学图书馆

Data imputation via conditional generative adversarial network with fuzzy c mean membership based loss term

APPLIED INTELLIGENcE 2022年第6期52卷 5912-5921页

作者： Wu, Zisheng Ling, Bingo Wing-Kuen Guangdong Univ Technol Fac Informat Engn Guangzhou 510006 Peoples R China

There are some missing values in the data when the data is acquired from the sensors or other equipments. This makes it difficult for performing the analysis based on the data. There are two major types of existing methods for performing the data imputation. They are the discriminative methods and the generative methods. However, these methods are incapable for dealing the data either with a high missing rate or with an unacceptable error. This paper proposes an effective method for performing the data imputation. In particular, the conditional generative adversarial network (cGAN) is used to predict the missing data. Here, the enhanced fuzzy c mean algorithm is employed for performing the clustering so that the information on the local samples is exploited in the algorithm. The computer numerical simulations are performed on several real world datasets. Since this cGAN exploits the class of the missing values of the data, it is shown that our proposed method achieves a higher imputation accuracy compared to state of the art methods.

关键词： fuzzy c mean algorithm Data imputation conditional generative adversarial network

来源：评论

学校读者我要写书评

暂无评论

Research based on neural Network information fusion model

引用

Liaoning Gongcheng Jishu Daxue Xuebao (Ziran Kexue Ban)/Journal of Liaoning Technical University (Natural Science Edition) 2007年第SUPPL. 2期26卷 173-175页

作者： Liu, Xiao-Yue Feng, Su-Min College of Computer and Automatic Control Hebei Polytechnic University Hebei 063009 China

In order to solve the problem that is difficult to establish the model of the huge data complex industrial production process. Propose fusion algorithm that based pn the topology of the Potential Field algorithm and fuzzy c mean algorithm, the result indicate: through fuse twice cluster algorithm, obtain the precise clustered number and the, determine the fuzzy neural network's structure, and according to that membership degree, construct the neural network model based on multi-criterion information fusion and the fuzzy technology, through the actual simulation on coal mining production process, the result confirms that the model is valid. This achievement has certain reference value and the guiding sense to the coal mining.

关键词： fuzzy c mean algorithm fuzzy neural network Information fusion Potential field algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：