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Dynamic Artificial Neural Network (DANN) MATLAB Toolbox for Time Series Analysis and Prediction

Khim Chhantyal
Faculty of Technology, Natural Sciences, and Maritime Sciences, University College of Southeast Norway

Minh Hoang
Faculty of Technology, Natural Sciences, and Maritime Sciences, University College of Southeast Norway

Håkon Viumdal
Faculty of Technology, Natural Sciences, and Maritime Sciences, University College of Southeast Norway

Saba Mylvaganam
Faculty of Technology, Natural Sciences, and Maritime Sciences, University College of Southeast Norway

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp17142568

Ingår i: Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016

Linköping Electronic Conference Proceedings 142:83, s. 568-574

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Publicerad: 2018-12-19

ISBN: 978-91-7685-399-3

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

MATLAB® Neural Network (NN) Toolbox can handle both static and dynamic neural networks. Using MATLAB® NN Toolbox with recurrent neural networks is not straight forward. We present a Dynamic Arti?cial Neural Network (DANN) MATLAB toolbox capable of handling fully connected neural networks for time-series analysis and predictions. Three different learning algorithms are incorporated in the MATLAB DANN toolbox: Back Propagation Through Time (BPTT) an of?ine learning algorithm and two online learning algorithms; Real Time Recurrent Learning (RTRL) and Extended Kalman Filter (EKF). In contrast to existing MATLAB® NN Toolbox, the presented MATLAB DANN toolbox has a possibility to perform the optimal tuning of network parameters using grid search method. Three different cases are used for testing three different learning algorithms. The simulation studies con?rm that the developed MATLAB DANN toolbox can be easily used in time-series prediction applications successfully. Some of the essential features of the learning algorithms are seen in the graphical user interfaces discussed in the paper. In addition, installation guide for the MATLAB DANN toolbox is also given.

Nyckelord

dynamic arti?cial neural network (DANN), back propagation through time (BPTT), real-time recurrent learning (RTRL), extended Kalman filter (EKF), time series

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