The theoretical foundations of statistical learning theory based on fuzzy random samples in Sugeno measure space

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331211403796 ◽

2011 ◽

Vol 34 (5) ◽

pp. 520-526 ◽

Author(s):

Ha Minghu ◽

Wang Chao ◽

Witold Pedrycz

Keyword(s):

Statistical Learning ◽

Learning Theory ◽

Measure Space ◽

Statistical Learning Theory ◽

Random Samples ◽

Sugeno Measure ◽

Theoretical Foundations ◽

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The theoretical foundations of statistical learning theory based on fuzzy number samples

Information Sciences ◽

10.1016/j.ins.2008.03.025 ◽

2008 ◽

Vol 178 (16) ◽

pp. 3240-3246 ◽

Author(s):

Ming-Hu Ha ◽

Jing Tian

Keyword(s):

Statistical Learning ◽

Learning Theory ◽

Fuzzy Number ◽

Statistical Learning Theory ◽

Theoretical Foundations

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The Key Theorem of Learning Theory Based on Sugeno Measure and Fuzzy Random Samples

Lecture Notes in Computer Science - Life System Modeling and Intelligent Computing ◽

10.1007/978-3-642-15597-0_27 ◽

2010 ◽

pp. 241-249 ◽

Author(s):

Minghu Ha ◽

Chao Wang ◽

Witold Pedrycz

Keyword(s):

Learning Theory ◽

Random Samples ◽

The Key Theorem ◽

Sugeno Measure ◽

Key Theorem ◽

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Universal Consistency and Bloat in GP Some theoretical considerations about Genetic Programming from a Statistical Learning Theory viewpoint

Revue d intelligence artificielle ◽

10.3166/ria.20.805-827 ◽

2006 ◽

Vol 20 (6) ◽

pp. 805-827 ◽

Author(s):

Sylvain Gelly ◽

Olivier Teytaud ◽

Nicolas Bredeche ◽

Marc Schoenauer

Keyword(s):

Genetic Programming ◽

Statistical Learning ◽

Learning Theory ◽

Statistical Learning Theory ◽

Universal Consistency ◽

Theoretical Considerations

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Practical use of statistical learning theory for modeling freezing point depression of electrolyte solutions: LSSVM model

Journal of Natural Gas Science and Engineering ◽

10.1016/j.jngse.2014.06.020 ◽

2014 ◽

Vol 20 ◽

pp. 414-421 ◽

Author(s):

Hamidreza Yarveicy ◽

Ali Kariman Moghaddam ◽

Mohammad M. Ghiasi

Keyword(s):

Statistical Learning ◽

Learning Theory ◽

Freezing Point ◽

Statistical Learning Theory ◽

Electrolyte Solutions ◽

Freezing Point Depression

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Tuning of neural networks based on genetic algorithm and statistical learning theory

Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826) ◽

10.1109/icmlc.2004.1378565 ◽

2005 ◽

Author(s):

En-hui Zheng ◽

Min Yang

Keyword(s):

Genetic Algorithm ◽

Neural Networks ◽

Statistical Learning ◽

Learning Theory ◽

Statistical Learning Theory

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Statistical Learning Theory

Technometrics ◽

10.1080/00401706.1999.10485951 ◽

1999 ◽

Vol 41 (4) ◽

pp. 377-378 ◽

Author(s):

Yuhai Wu

Keyword(s):

Statistical Learning ◽

Learning Theory ◽

Statistical Learning Theory

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Application of statistical learning theory to predict corrosion rate of injecting water pipeline

9th IEEE International Conference on Cognitive Informatics (ICCI'10) ◽

10.1109/coginf.2010.5599754 ◽

2010 ◽

Author(s):

Huang Zhen ◽

Liu Hong ◽

Fan Mujiao ◽

Xu Chunbi

Keyword(s):

Corrosion Rate ◽

Statistical Learning ◽

Learning Theory ◽

Statistical Learning Theory ◽

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Multiparameter Regularization for Construction of Extrapolating Estimators in Statistical Learning Theory

Multiscale Signal Analysis and Modeling ◽

10.1007/978-1-4614-4145-8_15 ◽

2012 ◽

pp. 347-366 ◽

Author(s):

Shuai Lu ◽

Sergiy Pereverzyev ◽

Sivananthan Sampath

Keyword(s):

Statistical Learning ◽

Learning Theory ◽

Statistical Learning Theory

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Statistical Learning Theory: A Pack-based Strategy for Uncertain Feasibility and Optimization Problems

Lecture Notes in Control and Information Sciences - Recent Advances in Learning and Control ◽

10.1007/978-1-84800-155-8_1 ◽

2007 ◽

pp. 1-14 ◽

Author(s):

Teodoro Alamo ◽

Roberto Tempo ◽

Eduardo F.

Keyword(s):

Statistical Learning ◽

Learning Theory ◽

Optimization Problems ◽

Statistical Learning Theory

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Early damage warning of railway bridge in time-domain based on statistical learning theory

Bridge Maintenance, Safety, Management and Life Extension ◽

10.1201/b17063-61 ◽

2014 ◽

pp. 437-444

Author(s):

D Shan ◽

Z Huang ◽

I Khan ◽

C Fu

Keyword(s):

Statistical Learning ◽

Learning Theory ◽

Time Domain ◽

Statistical Learning Theory ◽

Railway Bridge ◽

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