Abstract
Due to the difficulty in describing the nonlinear characteristics of a movable propeller turbine, this paper introduces the construction and simulation of the movable propeller turbine neural network model ZZ587. The convergence speed of the offline training is fast and the accuracy of the model is high when using the Levenberg-Marquardt algorithm. Matlab and Simulink are used for the nonlinear simulation of the movable propeller turbine neural network model ZZ587. The variability of the different inner parameters of the system and the turbine can be attained quickly and with integrity. It provides a good base for the research of control policy of the movable propeller turbine governing system.
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© 2006 Springer-Verlag Berlin Heidelberg
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Chang, J., Peng, Y. (2006). Construction and Simulation of the Movable Propeller Turbine Neural Network Model. In: Yeung, D.S., Liu, ZQ., Wang, XZ., Yan, H. (eds) Advances in Machine Learning and Cybernetics. Lecture Notes in Computer Science(), vol 3930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11739685_14
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DOI: https://doi.org/10.1007/11739685_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33584-9
Online ISBN: 978-3-540-33585-6
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