Guang Pu Xue Yu Guang Pu Fen Xi Guang Pu, Mar 1, 2014
The near infrared (NIR) spectrum contains a global signature of composition, and enables to predi... more The near infrared (NIR) spectrum contains a global signature of composition, and enables to predict different proper ties of the material. In the present paper, a genetic algorithm and an adaptive modeling technique were applied to build a multiobjective least square support vector machine (MLS-SVM), which was intended to simultaneously determine the concentrations of multiple components by NIR spectroscopy. Both the benchmark corn dataset and self-made Forsythia suspense dataset were used to test the proposed approach. Results show that a genetic algorithm combined with adaptive modeling allows to efficiently search the LS-SVM hyperparameter space. For the corn data, the performance of multi-objective LS-SVM was significantly better than models built with PLS1 and PLS2 algorithms. As for the Forsythia suspense data, the performance of multi-objective LS-SVM was equivalent to PLS1 and PLS2 models. In both datasets, the over-fitting phenomena were observed on RBFNN models. The single objective LS-SVM and MLS-SVM didn't show much difference, but the one-time modeling convenience al lows the potential application of MLS-SVM to multicomponent NIR analysis.
A smart adaptive algorithm is presented to model the spectral response of general passive planar ... more A smart adaptive algorithm is presented to model the spectral response of general passive planar electrical structures over a frequency range of interest, based on a limited number of data samples. Rational (pole-zero) functions are used to model and interpolate the S-parameter data obtained through full-wave electro-magnetic simulations. The adaptive algorithm doesn’t require any a priori knowledge of the dynamics of the system to select an appropriate sample distribution and an appropriate model complexity.
New modeling technology is developed that allows engineers to define the frequency range, layout ... more New modeling technology is developed that allows engineers to define the frequency range, layout parameters, material properties and desired accuracy for automatic generation of simulation models of general passive electrical structures. It combines electromagnetic (EM) accuracy of parameterized passive models with the simulation speed of analytical models. The adaptive algorithm doesn’t require any a priori knowledge of the dynamics of the system to select an appropriate sample distribution and an appropriate model complexity. With this technology, designers no longer must put up with legacy modeling techniques or invest resources in examining new ones.
ABSTRACT Metamodelling offers an efficient way to imitate the behaviour of computationally expens... more ABSTRACT Metamodelling offers an efficient way to imitate the behaviour of computationally expensive simulators. Kriging based metamodels are popular in approximating computation-intensive simulations of deterministic nature. Irrespective of the existence of various variants of Kriging in the literature, only a handful of Kriging implementations are publicly available and most, if not all, free libraries only provide the standard Kriging metamodel. ooDACE toolbox offers a robust, flexible and easily extendable framework where various Kriging variants are implemented in an object-oriented fashion under a single platform. This paper presents an incremental update of the ooDACE toolbox introducing an implementation of Gradient Enhanced Kriging which has been tested and validated on several engineering problems.
A new adaptive technique is presented for building accurate and stable Partial Element Equivalent... more A new adaptive technique is presented for building accurate and stable Partial Element Equivalent Circuit (PEEC) models over a wide frequency range. Ra-tional models are generated for impedances corresponding to partial inductances and coefficients of potential over a frequency range of interest, based on a limited number of samples. Delay extraction is applied in order to keep the order of the rational models as low as possible. The adaptive algorithm doesn't require any a-priori knowledge of the dynamics of the system to select an appropriate sample distribution and an appropriate model complexity.
This paper describes an iterative rational least-squares method, which is used for accurate trans... more This paper describes an iterative rational least-squares method, which is used for accurate transfer function synthesis of frequency-domain continuous-time systems. The identification method starts from an initial set of prescribed poles, and relocates them using a Sanathanan-Koerner iteration in order to minimize the global fitting error. Orthonormal rational functions are used to improve the numerical conditioning of the system equations. The method is computationally very efficient, and the calculated transfer function is very lenient towards accurate extraction of poles and zeros.
Guang Pu Xue Yu Guang Pu Fen Xi Guang Pu, Mar 1, 2014
The near infrared (NIR) spectrum contains a global signature of composition, and enables to predi... more The near infrared (NIR) spectrum contains a global signature of composition, and enables to predict different proper ties of the material. In the present paper, a genetic algorithm and an adaptive modeling technique were applied to build a multiobjective least square support vector machine (MLS-SVM), which was intended to simultaneously determine the concentrations of multiple components by NIR spectroscopy. Both the benchmark corn dataset and self-made Forsythia suspense dataset were used to test the proposed approach. Results show that a genetic algorithm combined with adaptive modeling allows to efficiently search the LS-SVM hyperparameter space. For the corn data, the performance of multi-objective LS-SVM was significantly better than models built with PLS1 and PLS2 algorithms. As for the Forsythia suspense data, the performance of multi-objective LS-SVM was equivalent to PLS1 and PLS2 models. In both datasets, the over-fitting phenomena were observed on RBFNN models. The single objective LS-SVM and MLS-SVM didn't show much difference, but the one-time modeling convenience al lows the potential application of MLS-SVM to multicomponent NIR analysis.
A smart adaptive algorithm is presented to model the spectral response of general passive planar ... more A smart adaptive algorithm is presented to model the spectral response of general passive planar electrical structures over a frequency range of interest, based on a limited number of data samples. Rational (pole-zero) functions are used to model and interpolate the S-parameter data obtained through full-wave electro-magnetic simulations. The adaptive algorithm doesn’t require any a priori knowledge of the dynamics of the system to select an appropriate sample distribution and an appropriate model complexity.
New modeling technology is developed that allows engineers to define the frequency range, layout ... more New modeling technology is developed that allows engineers to define the frequency range, layout parameters, material properties and desired accuracy for automatic generation of simulation models of general passive electrical structures. It combines electromagnetic (EM) accuracy of parameterized passive models with the simulation speed of analytical models. The adaptive algorithm doesn’t require any a priori knowledge of the dynamics of the system to select an appropriate sample distribution and an appropriate model complexity. With this technology, designers no longer must put up with legacy modeling techniques or invest resources in examining new ones.
ABSTRACT Metamodelling offers an efficient way to imitate the behaviour of computationally expens... more ABSTRACT Metamodelling offers an efficient way to imitate the behaviour of computationally expensive simulators. Kriging based metamodels are popular in approximating computation-intensive simulations of deterministic nature. Irrespective of the existence of various variants of Kriging in the literature, only a handful of Kriging implementations are publicly available and most, if not all, free libraries only provide the standard Kriging metamodel. ooDACE toolbox offers a robust, flexible and easily extendable framework where various Kriging variants are implemented in an object-oriented fashion under a single platform. This paper presents an incremental update of the ooDACE toolbox introducing an implementation of Gradient Enhanced Kriging which has been tested and validated on several engineering problems.
A new adaptive technique is presented for building accurate and stable Partial Element Equivalent... more A new adaptive technique is presented for building accurate and stable Partial Element Equivalent Circuit (PEEC) models over a wide frequency range. Ra-tional models are generated for impedances corresponding to partial inductances and coefficients of potential over a frequency range of interest, based on a limited number of samples. Delay extraction is applied in order to keep the order of the rational models as low as possible. The adaptive algorithm doesn't require any a-priori knowledge of the dynamics of the system to select an appropriate sample distribution and an appropriate model complexity.
This paper describes an iterative rational least-squares method, which is used for accurate trans... more This paper describes an iterative rational least-squares method, which is used for accurate transfer function synthesis of frequency-domain continuous-time systems. The identification method starts from an initial set of prescribed poles, and relocates them using a Sanathanan-Koerner iteration in order to minimize the global fitting error. Orthonormal rational functions are used to improve the numerical conditioning of the system equations. The method is computationally very efficient, and the calculated transfer function is very lenient towards accurate extraction of poles and zeros.
Uploads
Papers by Tom Dhaene