A System Identification Method for Linear Regression Models Based on Support Vector Machine

Transactions of the Society of Instrument and Control Engineers

doi 10.9746/sicetr1965.37.1189

Full Text

Abstract

Available in

Date

Authors

Publisher

The Society of Instrument and Control Engineers

Related search

On-Line Support Vector Machine Regression

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2002English

Algorithm of Fuzzy Support Vector Machine Based on a Piecewise Linear Fuzzy Weight Method

International Journal of Cognitive Informatics and Natural Intelligence
Human-Computer InteractionArtificial IntelligenceSoftware
2018English

BSP-Based Support Vector Regression Machine Parallel Framework

International Journal of Networked and Distributed Computing
Computer NetworksComputer Science ApplicationsCommunications
2013English

Application Research for Ultrasonic Flaw Identification Based on Support Vector Machine

2015English

Regression Depth and Support Vector Machine

Data Depth: Robust Multivariate Analysis, Computational Geometry and Applications
2006English

Machine Learning Scoring Functions Based on Random Forest and Support Vector Regression

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2012English

The Method of Applying Support Vector Machine to Engineering Data Regression

2015English

ViralmiR: A Support-Vector-Machine-Based Method for Predicting Viral microRNA Precursors

BMC Bioinformatics
BiochemistryApplied MathematicsComputer Science ApplicationsStructural BiologyMolecular Biology
2015English

Linear Regression and Support Vector Machine for Classification of E-Learning Students’ Engagement and Performance

International Journal of Engineering and Advanced Technology
EngineeringComputer Science ApplicationsEnvironmental Engineering
2019English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2026 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy