An Easy-to-Implement Hysteresis Model Identification Method Based on Support Vector Regression

IEEE Transactions on Magnetics ◽

10.1109/tmag.2017.2702168 ◽

2017 ◽

Vol 53 (11) ◽

pp. 1-4 ◽

Author(s):

Shukuan Zhang ◽

Mingqiao Wang ◽

Ping Zheng ◽

Guangyuan Qiao ◽

Faliang Liu ◽

...

Keyword(s):

Support Vector Regression ◽

Model Identification ◽

Support Vector ◽

Hysteresis Model ◽

Identification Method

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Hysteresis model identification based on support vector regression

2017 IEEE International Magnetics Conference (INTERMAG) ◽

10.1109/intmag.2017.8007608 ◽

2017 ◽

Author(s):

P. Zheng ◽

S. Zhang

Keyword(s):

Support Vector Regression ◽

Model Identification ◽

Support Vector ◽

Hysteresis Model

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Support vector regression for Hammerstein-Wiener model identification

2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16) ◽

10.1109/icctide.2016.7725370 ◽

2016 ◽

Author(s):

C. Karthik ◽

A. Ramalakshmi ◽

K. Valarmathi

Keyword(s):

Support Vector Regression ◽

Model Identification ◽

Support Vector ◽

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Online model identification for underwater vehicles through incremental support vector regression

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ◽

10.1109/iros.2017.8206278 ◽

2017 ◽

Author(s):

Bilal Wehbe ◽

Alexander Fabisch ◽

Mario Michael Krell

Keyword(s):

Support Vector Regression ◽

Model Identification ◽

Underwater Vehicles ◽

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Wiener model identification of blast furnace ironmaking process based on Laguerre filter and linear programming support vector regression

2014 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2014.6889725 ◽

2014 ◽

Author(s):

Xia Xu ◽

Changchun Hua ◽

Yinggan Tang ◽

Xinping Guan

Keyword(s):

Linear Programming ◽

Blast Furnace ◽

Support Vector Regression ◽

Model Identification ◽

Support Vector ◽

Wiener Model ◽

Blast Furnace Ironmaking ◽

Programming Support ◽

Laguerre Filter ◽

Ironmaking Process

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Experimental verification of the support vector regression based structural identification method by using shaking table test data

Structural Control and Health Monitoring ◽

10.1002/stc.209 ◽

2008 ◽

Vol 15 (4) ◽

pp. 505-517 ◽

Author(s):

Jian Zhang ◽

Tadanobu Sato

Keyword(s):

Support Vector Regression ◽

Test Data ◽

Experimental Verification ◽

Shaking Table Test ◽

Structural Identification ◽

Shaking Table ◽

Support Vector ◽

Identification Method

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A New Hyperparameters Identification Method of Support Vector Regression Model Based on Back Propagation Neural Network

2020 Global Reliability and Prognostics and Health Management (PHM-Shanghai) ◽

10.1109/phm-shanghai49105.2020.9280989 ◽

2020 ◽

Author(s):

Yongtang Ye ◽

Wenbo Zhang ◽

Kunsong Lin ◽

Ping Xu ◽

Yunxia Chen

Keyword(s):

Neural Network ◽

Regression Model ◽

Support Vector Regression ◽

Back Propagation ◽

Back Propagation Neural Network ◽

Support Vector ◽

Support Vector Regression Model ◽

Identification Method ◽

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Hybrid kernel identification method based on support vector regression and regularisation network algorithms

IET Signal Processing ◽

10.1049/iet-spr.2013.0242 ◽

2014 ◽

Vol 8 (9) ◽

pp. 981-989 ◽

Author(s):

Okba Taouali ◽

Ilyes Elaissi ◽

Hassani Messaoud

Keyword(s):

Support Vector Regression ◽

Support Vector ◽

Network Algorithms ◽

Identification Method ◽

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Model identification of thermal object based on smooth support vector regression

2007 International Conference on Wavelet Analysis and Pattern Recognition ◽

10.1109/icwapr.2007.4421651 ◽

2007 ◽

Author(s):

Chao Zhao ◽

Pu Han

Keyword(s):

Support Vector Regression ◽

Model Identification ◽

Support Vector ◽

Object Based ◽

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Local and Regional Hour-Ahead Forecasts of Solar Irradiance with Training Data Selection and Support Vector Regression

IEEJ Transactions on Power and Energy ◽

10.1541/ieejpes.136.898 ◽

2016 ◽

Vol 136 (12) ◽

pp. 898-907 ◽

Author(s):

Joao Gari da Silva Fonseca Junior ◽

Hideaki Ohtake ◽

Takashi Oozeki ◽

Kazuhiko Ogimoto

Keyword(s):

Support Vector Regression ◽

Solar Irradiance ◽

Training Data ◽

Data Selection ◽

Support Vector ◽

Training Data Selection

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Performance Comparison of Generalized Regression Network, Radial Basis Function Network and Support Vector Regression for Wind Power Forecasting

International Review on Modelling and Simulations (IREMOS) ◽

10.15866/iremos.v12i1.15781 ◽

2019 ◽

Vol 12 (1) ◽

pp. 16

Author(s):

Jyothi Varanasi ◽

Madan Mohan Tripathi

Keyword(s):

Radial Basis Function ◽

Support Vector Regression ◽

Basis Function ◽

Radial Basis Function Network ◽

Performance Comparison ◽

Support Vector ◽

Wind Power Forecasting ◽

Radial Basis ◽

Function Network

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