System identification based on Support Kernels Regression
نویسندگان
چکیده
This paper deals with the identification of nonlinear systems using multi-kernel approach. In this context, we have improved the Support Vector Regression (SVR) method in order to identify nonlinear complex system. Our idea consists in dividing the regressor vector in several blocks, and, for each one a kernel function is used. This blockwise SVR approach is called Support Kernel Regression (SKR). Furthermore, we have proposed two methods SKR(lin-rbf) and SKR(rbf-rbf). In these two methods we have divided the regressor into two Blocks. In the SKR(lin-rbf) based approach, the linear kernel and the Gaussian kernel are used, respectively, to identify the influence of the first block and of the second block on the model. However, in the SKR(rbf-rbf) approach two gaussian kernels are used. An example is presented for qualitative comparison with the classical SVR approach based on a single kernel function. The results reveal the accuracy and the robustness of the obtained model based on our proposed approaches. Keywords—Support Vector Regression; Support Kernel Regression; Nonlinear System Identification; Kernel Function
منابع مشابه
Ensemble Kernel Learning Model for Prediction of Time Series Based on the Support Vector Regression and Meta Heuristic Search
In this paper, a method for predicting time series is presented. Time series prediction is a process which predicted future system values based on information obtained from past and present data points. Time series prediction models are widely used in various fields of engineering, economics, etc. The main purpose of using different models for time series prediction is to make the forecast with...
متن کاملDevelopment of a Pharmacogenomics Model based on Support Vector Regression with Optimal Features Selection Approach to Determine the Initial Therapeutic Dose of Warfarin Anticoagulant Drug
Introduction: Using artificial intelligence tools in pharmacogenomics is one of the latest bioinformatics research fields. One of the most important drugs that determining its initial therapeutic dose is difficult is the anticoagulant warfarin. Warfarin is an oral anticoagulant that, due to its narrow therapeutic window and complex interrelationships of individual factors, the selection of its ...
متن کاملDevelopment of a Pharmacogenomics Model based on Support Vector Regression with Optimal Features Selection Approach to Determine the Initial Therapeutic Dose of Warfarin Anticoagulant Drug
Introduction: Using artificial intelligence tools in pharmacogenomics is one of the latest bioinformatics research fields. One of the most important drugs that determining its initial therapeutic dose is difficult is the anticoagulant warfarin. Warfarin is an oral anticoagulant that, due to its narrow therapeutic window and complex interrelationships of individual factors, the selection of its ...
متن کاملTwitter Language Identification using Rational Kernels and its potential application to Sociolinguistics
This paper describes the techniques used by the system presented at the TweetLID shared task for Twitter language identification. The system is based on Support Vector Machines and Rational Kernels. An algorithm for multilanguage labeling is described. Its evaluation and application to Sociolinguistics is also included.
متن کاملIdentification and Adaptive Position and Speed Control of Permanent Magnet DC Motor with Dead Zone Characteristics Based on Support Vector Machines
In this paper a new type of neural networks known as Least Squares Support Vector Machines which gained a huge fame during the recent years for identification of nonlinear systems has been used to identify DC motor with nonlinear dead zone characteristics. The identified system after linearization in each time span, in an online manner provide the model data for Model Predictive Controller of p...
متن کامل