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Asymptotic Optimality of the nonnegative garrote Estimator Under Heteroscedastic Errors

Journal of Systems Science & Complexity 2020年第2期33卷 545-562页

作者： CHEN Xiuping CAI Guanghui GAO Yan ZHAO Shangwei College of Statistics and Mathematics Zhejiang Gongshang UniversityHangzhou 310018China Department of Statistics College of ScienceMinzu University of ChinaBeijing 100081China

This paper proposes the nonnegative garrote(NG)estimator for linear model with heteroscedastic *** the other hand,under some regularity conditions,the authors show the asymptotic optimality of the NG estimator by referring to the idea of the asymptotic optimality of the model average *** results and a real data analysis are reported for testing the results obtained *** results provide a stronger theoretical basis for the use of NG estimator by strengthening existing findings.

关键词： Asymptotic optimality coefficient shrinkage heteroscedastic errors nonnegative garrote

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A nonnegative garrote-based Method for Multivariate Fault Isolation

A Nonnegative Garrote-based Method for Multivariate Fault Is...

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第36届中国控制会议

作者： Yi-Min Guo Jian-Guo Wang Bang-Hua Yang Shi-Wei Ma Min-Rui Fei Li-Lan Liu Hui Xu Yuan Yao Yi-Ping Wu School of Mechatronical Engineering and Automation Shanghai UniversityShanghai Key Lab of Power Station Automation Technology Department of Chemical Engineering National Tsing-Hua University Shanghai Baosight Software Co Ltd

ISBN: (纸本)9781538629185

Fault isolation is an essential step in multivariate statistical process monitoring,which discovers the cause of the detected *** common adopted techniques for fault isolation,such as contribution plots,reconstruction analysis,branch and bound,etc.,often suffer from the problems of the smearing effect,insufficient historical fault data,and heavy computational *** this paper,the nonnegative garrote（NNG） estimator is utilized for multivariate statistical fault isolation,which solves the problems of the existing *** proposed method is based on the finding that there is equivalence between fault isolation and variable selection in discriminant *** from the existing methods,the NNG-based fault isolation method does not suggest a single set of faulty ***,it provides a sequence of process variables according to their responsibilities for the detected *** results are informative for diagnosing the root cause of the fault.

关键词： Fault isolation Variable selection nonnegative garrote Process monitoring

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Group sparse representation for image categorization and semantic video retrieval

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Science China(Information Sciences) 2011年第10期54卷 2051-2063页

作者： LIU YaNan 1,2 ,WU Fei 2 & ZHUANG YueTing 2 1 School of Information,Zhejiang University of Finance & Economics,Hangzhou,310018,China 2 College of Computer Science and Technology,Zhejiang University,Hangzhou,310012,China School of Information Zhejiang University of Finance & Economics College of Computer Science and Technology Zhejiang University

Multimedia content analysis and management are a promising and challenging *** this paper we develop a novel approach to image representation,which we call group sparse representation (GSR),for image classification and video *** basic idea is to represent a test image as a weighted combination of all the training *** particular,we introduce two sets of weight coefficients,one for each training image and the other for each ***,we formulate our concern as a group nonnegative garrote *** resulting representations are sparse,and they are appropriate for discriminant *** on Caltech101 and PASCAL VOC2008 image dataset and TRECVID2005 video corpus testify that our proposed approach is efficient and effective.

关键词： compressive sensing group sparse representation bag-of-SIFT-words nonnegative garrote l1-minimization apcluster

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Development of input variable selection and structural optimization algorithm for recurrent neural network

Development of input variable selection and structural optim...

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第40届中国控制会议

作者： Mengyan Zhang Lin Sui Kai Sun School of Electrical Engineering and Automation Qilu University of Technology （Shandong Academy of Sciences）

With the rapid development of industrial field data acquisition and storage systems, neural networks have been widely used to handle complex nonlinear processes and establish data-driven models. In these situations, the time-dependent correlation between process variables and target variables is essential. The performance of data-driven models will worse when the timeseries characteristics are omitted. Considering this problem, the paper proposes an input variable selection and structure optimization algorithm for recurrent neural network（RNN） with nonnegative garrote（NNG）. The recurrent neural network deals with the strong nonlinearity and dynamic characteristics of the industrial process by obtaining time information from the sequence data. The NNG algorithm shrinks the input weights of RNN and then selects the input variables and optimizes the hidden layers. By taking an artificial data set as an example and comparing it to other algorithms, the effectiveness of the developed algorithm is verified.

关键词： Recurrent neural network nonnegative garrote variable selection nonlinear regression time-series

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Soft Sensor Approach for Optimal Operation of Cooling Tower for Energy Conservation

Soft Sensor Approach for Optimal Operation of Cooling Tower ...

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第26届中国控制与决策会议

作者： Jian-Guo Wang Qian-Ping Xiao Juan-Juan Wang Shi-Wei Ma Wen-Tao Rao Yong-Jie Zhang School of Mechatronical Engineering and Automation Shanghai UniversityShanghai Key Lab of Power Station Automation Technology Institute of Environment & Resources Baosteel Research Institute

This paper presents a data-driven adaptive soft sensor approach to investigate the performance and optimal operation of cooling tower for energy conservation. To achieve this aim, first, the cooling tower process is characterized by an adaptive soft sensor with nonnegative garrote（NNG） variable selection procedure. Then, based on the statistics result of NNG variable selection, the effect of environment temperature and humidity on the cooling capacity was investigated by principal component analysis（PCA）. At last, the optimal strategy of fan operation mode was presented and the implementation of the optimal strategy was investigated for a cooling tower, which showed that there was large room for energy conservation.

关键词： nonnegative garrote variable selection soft sensor cooling tower energy conservation

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