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1. An improved multi-task least squares twin support vector machine NSTL国家科技图书文献中心

Hossein Moosaei |  Fatemeh Bazikar... -  《Annals of mathematics and artificial intelligence》 - 2025,93(1) - 21~41 - 共21页

摘要: squares twin support vector machine (MTLS-TSVM) was |  direct multi-task twin support vector machine (DMTSVM |  twin support vector machine (IMTLS-TSVM). IMTLS-TSVM |  become a popular field in machine learn-ing and has a | In recent years, multi-task learning (MTL) has
关键词: Least squares |  Multi-task learning |  Twin support vector machine |  Multi-task twin support vector machine |  Quadratic programming problems

2. A novel fuzzy twin support vector machine using mass-based dissimilarity measure NSTL国家科技图书文献中心

Wang, Xia |  Wu, Gaohao... -  《Knowledge and information systems》 - 2025,67(5) - 4233~4300 - 共68页

摘要: fuzzy twin support vector machine (FTSVM). However |  machine, TWSVM, FTSVM, twin bounded support vector |  dissimilarity measure, and fuzzy twin support vector machine |  twin support vector machines (TWSVM), researchers |  compared to support vector machine, fuzzy support vector
关键词: Mass-based dissimilarity measure |  Isolate tree |  Fuzzy membership function |  Twin support vector machine |  Coordinate descent strategy

3. GL-TSVM: A Robust and Smooth Twin Support Vector Machine with Guardian Loss Function NSTL国家科技图书文献中心

Mushir Akhtar |  M. Tanveer... -  《Pattern Recognition,Part II》 -  International Conference on Pattern Recognition - 2025, - 63~78 - 共16页

摘要:Twin support vector machine (TSVM), a variant |  of support vector machine (SVM), has garnered |  significant attention due to its 3/4 times lower |  computational complexity compared to SVM. However, due to the |  utilization of the hinge loss function, TSVM is sensitive to
关键词: Support vector machine |  Twin support vector machine |  Robust classification |  Asymmetric loss function |  Iterative algorithm

4. Pipeline leak diagnosis using multisource multiscale attention entropy and enhanced least square twin support vector machine NSTL国家科技图书文献中心

Zhou, Hongbiao |  Zhang, Shilin... -  《Measurement Science & Technology》 - 2025,36(3) - 1~15 - 共15页

摘要: enhanced least-squares twin support vector machine |  vector is constructed by integrating MATE | To achieve rapid and precise identification of |  water supply pipeline leakage faults, this study |  introduces a diagnostic framework that integrates
关键词: pipeline leakage detection |  multisource fusion |  multiscale attention entropy |  enhanced least square twin support vector machine |  AdaBoost

5. Enhanced health states recognition for electric rudder system using optimized twin support vector machine NSTL国家科技图书文献中心

Chenxia Guo |  Hao Qin... -  《Quality and reliability engineering international》 - 2025,41(1) - 274~292 - 共19页

摘要: platform. The twin support vector machine (TWSVM) not | Abstract Safety and reliability represent |  indispensable prerequisites for electric rudder systems (ERS | ), while health states recognition serves as a potent |  technology that fortifies and optimizes these essential
关键词: Bat algorithm |  electric rudder system |  fruit fly optimization algorithm |  Health states recognition |  twin support vector machine

6. Hypergraph Regularized Semi-supervised Least Squares Twin Support Vector Machine for Multilabel Classification NSTL国家科技图书文献中心

Reshma Rastogi |  Dev Nirwal -  《Pattern Recognition,Part XXIV》 -  International Conference on Pattern Recognition - 2025, - 223~237 - 共15页

摘要: Least Squares Twin Support Vector Machine (KNNLSTSVM | . Multilabel twin support vector machines (MLTSVM) has become |  as Hypergraph Least Squares Twin Support Vector |  Machine for Multi-label Learning (HMLLSTSVM) wherein we | In a multi-label learning problem, each
关键词: Semi-supervised learning |  Hypergraph |  Laplacian matrix |  Multilabel learning

7. An efficient implicit Lagrangian twin bounded support vector machine NSTL国家科技图书文献中心

Umesh Gupta |  Deepak Gupta -  《International journal of advanced intelligence paradigms》 - 2025,30(1) - 36~68 - 共33页

摘要: Lagrangian twin bounded support vector machine based on |  using L2-norm of the vector of slack variable. Also | In this paper, an efficient implicit |  fuzzy membership is proposed with the dual formulation |  in order to reduce the sensitivity of noise and
关键词: TSVM |  twin support vector machine |  twin bounded support vector machine |  Lagrangian function |  iterative approaches |  fuzzy membership

8. Digital Twin for Health Monitoring of a Cantilever Beam Using Support Vector Machine NSTL国家科技图书文献中心

Vishnu Harikumar |  C. R. Bijudas -  《Journal of Vibration Engineering & Technologies》 - 2025,13(1 Pt.1) - 41~ - 共20页

摘要: develop a Digital Twin framework utilizing the Support |  Vector Machine classifier with second order polynomial |  analytics and artificial intelligence/machine learning (AI |  Vector Machines(SVM) for the Structural Health |  better accuracy of the proposed Digital Twin framework
关键词: Digital twin |  Support vector machine |  Structural health monitoring |  Surrogate modeling |  Transfer learning

9. A novel method for solving universum twin bounded support vector machine in the primal space NSTL国家科技图书文献中心

Hossein Moosaei |  Saeed Khosravi... -  《Annals of mathematics and artificial intelligence》 - 2025,93(1) - 131~150 - 共20页

摘要: related to Twin Bounded Support Vector Machines with | In supervised learning, the Universum, a third |  class that is not a part of either class in the |  classification task, has proven to be useful. In this study we |  propose (N(U)TBSVM), a Newton-based approach for solving
关键词: Twin bounded support vector machine |  Universum |  Newton's method |  Unconstrained optimization problem

10. An Unconstrained Primal Based Twin Parametric Insensitive Support Vector Regression NSTL国家科技图书文献中心

Gupta, Deepak |  Richhariya, Bharat... -  《International journal of uncertainty, fuzziness and knowledge-based systems》 - 2025,33(2) - 173~192 - 共20页

摘要: support vector machine. This is an efficient approach to |  parametric insensitive support vector regression (UPTPISVR |  regression algorithm based on primal formulation of twin |  computation time. The proposed method is termed as twin | In this paper, we propose an efficient
关键词: Twin support vector regression, prediction, unconstrained problem, parametric insensitive |  EXTREME LEARNING-MACHINE |  FINITE NEWTON METHOD |  STATISTICAL COMPARISONS |  CLASSIFIERS |  ENTROPY
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