Visualization of dynamics using local dynamic modelling with self organizing maps

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Abstract

In this work, we describe a procedure to visualize nonlinear process dynamics using a self-organizing map based local model dynamical estimator. The proposed method exploits the topology preserving nature of the resulting estimator to extract visualizations (planes) of insightful dynamical features, that allow to explore nonlinear systems whose behavior changes with the operating point. Since the visualizations are obtained from a dynamical model of the process, measures on the goodness of this estimator (such as RMSE or AIC) are also applicable as a measure of the trustfulness of the visualizations. To illustrate the application of the proposed method, an experiment to analyze the dynamics of a nonlinear system on different operating points is included. © Springer-Verlag Berlin Heidelberg 2007.

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Díaz-Blanco, I., Cuadrado-Vega, A. A., Diez-González, A. B., Fuertes-Martínez, J. J., Domínguez-González, M., & Reguera-Acevedo, P. (2007). Visualization of dynamics using local dynamic modelling with self organizing maps. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4668 LNCS, pp. 609–617). Springer Verlag. https://doi.org/10.1007/978-3-540-74690-4_62

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