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AUTOMATICA
2006
150views more  AUTOMATICA 2006»
13 years 4 months ago
Enlarging the terminal region of nonlinear model predictive control using the support vector machine method
In this paper, Receding Horizon Model Predictive Control (RHMPC) of nonlinear systems subject to input and state constraints is considered. We propose to estimate the terminal reg...
Chong Jin Ong, Dan Sui, Elmer G. Gilbert
AUTOMATICA
2005
108views more  AUTOMATICA 2005»
13 years 4 months ago
Enlarging the domain of attraction of MPC controllers
This paper presents a method for enlarging the domain of attraction of nonlinear model predictive control (MPC). The usual way of guaranteeing stability of nonlinear MPC is to add...
Daniel Limón, T. Alamo, Eduardo F. Camacho
BMCBI
2004
114views more  BMCBI 2004»
13 years 4 months ago
Profiled support vector machines for antisense oligonucleotide efficacy prediction
Background: This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises ...
Gustavo Camps-Valls, Alistair M. Chalk, Antonio J....
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
13 years 8 months ago
Controlling overfitting with multi-objective support vector machines
Recently, evolutionary computation has been successfully integrated into statistical learning methods. A Support Vector Machine (SVM) using evolution strategies for its optimizati...
Ingo Mierswa
ISCI
2008
165views more  ISCI 2008»
13 years 4 months ago
Support vector regression from simulation data and few experimental samples
This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
Gérard Bloch, Fabien Lauer, Guillaume Colin...