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Unsupervised feature selection via joint local learning and group sparse regression Regular Papers

Yue WU, Can WANG, Yue-qing ZHANG, Jia-jun BU

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 4,   Pages 538-553 doi: 10.1631/FITEE.1700804

Abstract: this issue, we propose a novel unsupervised feature selection algorithm via joint local learning and groupsparse regression (JLLGSR).JLLGSR incorporates local learning based clustering with group sparsity regularized regression in a singleformulation, and seeks features that respect both the manifold structure and group sparse structure

Keywords： Unsupervised     Local learning     Group sparse regression     Feature selection    

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Asystematic review of structured sparse learning Review

Lin-bo QIAO, Bo-feng ZHANG, Jin-shu SU, Xi-cheng LU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 4,   Pages 445-463 doi: 10.1631/FITEE.1601489

Abstract: from diverse scientific research fields and industrial development have led to increased interest in sparseStructured sparse learning encodes the structural information of the variables and has been quite successfulThese regularizations have greatly improved the efficacy of sparse learning algorithms through the useIn this article, we present a systematic review of structured sparse learning including ideas, formulationshierarchical image reconstruction, and in supervised learning in the context of a novel graph-guided logistic regression

Keywords： Sparse learning     Structured sparse learning     Structured regularization    

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Sparse fast Clifford Fourier transform Article

Rui WANG, Yi-xuan ZHOU, Yan-liang JIN, Wen-ming CAO

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 8,   Pages 1131-1141 doi: 10.1631/FITEE.1500452

Abstract: The sparse fast Fourier transform (sFFT) theory deals with the big data problem by using input data selectivelyThis has inspired us to create a new algorithm called sparse fast CFT (SFCFT), which can greatly improve

Keywords： Sparse fast Fourier transform (sFFT)     Clifford Fourier transform (CFT)     Sparse fast Clifford Fourier    

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Non-convex sparse optimization-based impact force identification with limited vibration measurements

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 3, doi: 10.1007/s11465-023-0762-2

Abstract: mn> regularization method often struggles to generate sparseMJX-TeXAtom-ORD">ℓ1 sparseTo alleviate such limitations, a novel non-convex sparse regularization method that uses the non-convexrealize simultaneous impact localization and time history reconstruction with an under-determined, sparse

Keywords： impact force identification     inverse problem     sparse regularization     under-determined condition     alternating    

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Uncertainty propagation analysis by an extended sparse grid technique

X. Y. JIA, C. JIANG, C. M. FU, B. Y. NI, C. S. WANG, M. H. PING

Frontiers of Mechanical Engineering 2019, Volume 14, Issue 1,   Pages 33-46 doi: 10.1007/s11465-018-0514-x

Abstract: In this paper, an uncertainty propagation analysis method is developed based on an extended sparse gridSubsequently, within the sparse grid numerical integration framework, the statistical moments of the

Keywords： uncertainty propagation analysis     extended sparse grid     maximum entropy principle     extended Gauss integration    

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Multiple regression models for energy consumption of office buildings in different climates in China

Siyu ZHOU, Neng ZHU

Frontiers in Energy 2013, Volume 7, Issue 1,   Pages 103-110 doi: 10.1007/s11708-012-0220-z

Abstract: Then on the basis of the simulated results, the multiple regression models were developed respectivelyAccording to the analysis of regression coefficients, the appropriate building envelope design schemesAt last, the regression model evaluations consisting of the simulation evaluations and the actual caseevaluations were performed to verify the feasibility and accuracy of the regression models.It is believed that the regression models developed in this paper can be used to estimate the energy

Keywords： regression model     energy consumption     building envelope     office building     different climates    

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A review of intelligent optimization for group scheduling problems in cellular manufacturing

Frontiers of Engineering Management   Pages 406-426 doi: 10.1007/s42524-022-0242-0

Abstract: Given that group technology can reduce the changeover time of equipment, broaden the productivity, andenhance the flexibility of manufacturing, especially cellular manufacturing, group scheduling problemsproduction cells in view of major setup times between groups and the other is how to schedule jobs in each groupoutlooks are given for outspread problems and problem algorithms for future research in the fields of group

Keywords： cellular manufacturing     group scheduling     flowshop     literature review    

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Laplacian sparse dictionary learning for image classification based on sparse representation Article

Fang LI, Jia SHENG, San-yuan ZHANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1795-1805 doi: 10.1631/FITEE.1600039

Abstract: Sparse representation is a mathematical model for data representation that has proved to be a powerfulAs one of the building blocks of the sparse representation method, dictionary learning plays an importantWe incorporate the Laplacian weighted graph in the sparse representation model and impose the l1-normAn LSD is a sparse overcomplete dictionary that can preserve the intrinsic structure of the data andResults show the advantages of the proposed LSD algorithm over state-of-the-art sparse representation

Keywords： Sparse representation     Laplacian regularizer     Dictionary learning     Double sparsity     Manifold    

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Dynamic response surface methodology using Lasso regression for organic pharmaceutical synthesis

Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 2,   Pages 221-236 doi: 10.1007/s11705-021-2061-y

Abstract: Two approaches can be adopted in the estimation of the model parameters: stepwise regression, used inseveral of previous publications, and Lasso regression, which is newly incorporated in this paper forTherefore, DRSM with Lasso regression can provide faster and more accurate data-driven models for a variety

Keywords： data-driven modeling     pharmaceutical organic synthesis     Lasso regression     dynamic response surface methodology    

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Interaction behavior and load sharing pattern of piled raft using nonlinear regression and LM algorithm-based

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 5,   Pages 1181-1198 doi: 10.1007/s11709-021-0744-6

Abstract: The obtained results are then checked statistically with nonlinear multiple regression (NMR) and artificial

Keywords： interaction     load sharing ratio     piled raft     nonlinear regression     artificial neural network    

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Multivariable regression model for Fox depth correction factor

Ravi Kant MITTAL, Sanket RAWAT, Piyush BANSAL

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 1,   Pages 103-109 doi: 10.1007/s11709-018-0474-6

Abstract: Therefore, this paper presents a non-linear regression model for the analysis of effect of embedment

Keywords： settlement     embedment     Fox depth correction factor     regression     multivariable    

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of driver-response relationships: identifying factors using a novel framework integrating quantile regression

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 6, doi: 10.1007/s11783-023-1676-2

Abstract:

● A novel framework integrating quantile regression with machine learning

Keywords： Driver-response     Upper boundary of relationship     Interpretable machine learning     Quantile regression    

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Emergence mechanisms of group consensus in social networks

Frontiers of Engineering Management doi: 10.1007/s42524-023-0277-x

Abstract: This article redefines group consensus as the emergence of collective intelligence resulting from self-organizingactions and interactions of individuals within a social network group.In our exploration of extant research on group consensus, we illuminate two frequently underestimatedThis process encompasses self-organized communication and interaction among group members, collectivelyguiding the group towards cognitive convergence and viewpoint integration.

Keywords： group consensus     social network     collective intelligence    

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compressive strength of soil-RAP blend stabilized with Portland cement using multivariate adaptive regression

Ali Reza GHANIZADEH, Morteza RAHROVAN

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 4,   Pages 787-799 doi: 10.1007/s11709-019-0516-8

Abstract: compressive strength (UCS) of soil-RAP blend stabilized with Portland cement based on multivariate adaptive regression

Keywords： soil-reclaimed asphalt pavement blend     Portland cement     unconfined compressive strength     multivariate adaptive regression    

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Determination of effective stress parameter of unsaturated soils: A Gaussian process regression approach

Pijush Samui, Jagan J

Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 2,   Pages 133-136 doi: 10.1007/s11709-013-0202-1

Abstract: This article examines the capability of Gaussian process regression (GPR) for prediction of effective

Keywords： unsaturated soil     effective stress parameter     Gaussian process regression (GPR)     artificial neural network    

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Title Author Date Type Operation

Unsupervised feature selection via joint local learning and group sparse regression

Yue WU, Can WANG, Yue-qing ZHANG, Jia-jun BU

Journal Article

Asystematic review of structured sparse learning

Lin-bo QIAO, Bo-feng ZHANG, Jin-shu SU, Xi-cheng LU

Journal Article

Sparse fast Clifford Fourier transform

Rui WANG, Yi-xuan ZHOU, Yan-liang JIN, Wen-ming CAO

Journal Article

Non-convex sparse optimization-based impact force identification with limited vibration measurements

Journal Article

Uncertainty propagation analysis by an extended sparse grid technique

X. Y. JIA, C. JIANG, C. M. FU, B. Y. NI, C. S. WANG, M. H. PING

Journal Article

Multiple regression models for energy consumption of office buildings in different climates in China

Siyu ZHOU, Neng ZHU

Journal Article

A review of intelligent optimization for group scheduling problems in cellular manufacturing

Journal Article

Laplacian sparse dictionary learning for image classification based on sparse representation

Fang LI, Jia SHENG, San-yuan ZHANG

Journal Article

Dynamic response surface methodology using Lasso regression for organic pharmaceutical synthesis

Journal Article

Interaction behavior and load sharing pattern of piled raft using nonlinear regression and LM algorithm-based

Journal Article

Multivariable regression model for Fox depth correction factor

Ravi Kant MITTAL, Sanket RAWAT, Piyush BANSAL

Journal Article

of driver-response relationships: identifying factors using a novel framework integrating quantile regression

Journal Article

Emergence mechanisms of group consensus in social networks

Journal Article

compressive strength of soil-RAP blend stabilized with Portland cement using multivariate adaptive regression

Ali Reza GHANIZADEH, Morteza RAHROVAN

Journal Article

Determination of effective stress parameter of unsaturated soils: A Gaussian process regression approach

Pijush Samui, Jagan J

Journal Article