Journal ArticleDOI
A New System Identification Method Based on Support Vector Machines
Shuichi Adachi,Tomonori Ogawa +1 more
TLDR
A new system identification method based on SVR is proposed for linear in parameter models and the effectiveness of the proposed method is examined through numerical examples.About:
This article is published in IFAC Proceedings Volumes.The article was published on 2001-08-01. It has received 13 citations till now. The article focuses on the topics: Relevance vector machine & Least squares support vector machine.read more
Citations
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Journal ArticleDOI
Support vector method for identification of Wiener models
TL;DR: In this article, support vector regression is applied to identify nonlinear systems represented by Wiener models, consisting of a linear dynamic system in series with a static nonlinear block, and the linear block is expanded in terms of basis functions, such as Laguerre or Kautz filters.
Journal ArticleDOI
Modelling of a surface marine vehicle with kernel ridge regression confidence machine
TL;DR: Results show that the application of conformal prediction provides an accurate model that reproduces with large accuracy the actual behaviour of the ship with confidence margins that ensure that the model response is within these margins, making it a suitable tool for system identification.
Journal ArticleDOI
Identification of a Surface Marine Vessel Using LS-SVM
TL;DR: The identification of the Nomoto second-order ship model with real experimental data obtained from a zig-zag manoeuvre made by a scale ship is demonstrated and validated through experimental tests that illustrate the potential of SVM for system identification.
Journal ArticleDOI
Identification of state-dependent parameter models with support vector regression
TL;DR: A support vector regression approach is presented for the identification of state-dependent parameter ARX models, whose parameters are described as functions of past inputs and outputs.
Journal ArticleDOI
Black-Box Marine Vehicle Identification with Regression Techniques for Random Manoeuvres
TL;DR: A number of regression techniques are used for black-box marine system identification of a scale ship, showing that machine learning techniques are robust approaches to model surface marine vehicles, even providing interpretable results in closed form equations using techniques such as symbolic regression.
References
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Book
The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Statistical learning theory
TL;DR: Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.
Journal ArticleDOI
Edger Set-up Model at Roughing Train in Hot Strip Mill
TL;DR: Shiiba et al. as mentioned in this paper developed a new mathematical model for edger set-up using measured values on a production mill, which is able to adjust the roll opening at each edger depending on a given distribution pattern of width reduction at each stand.