Utilization of Improved RBF Network in Modeling of Wave Energy Absorption System

Ying Zhang; Meng Xin Li; Ran Ran Wang

doi:10.4028/www.scientific.net/AMM.483.578

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 483Utilization of Improved RBF Network in Modeling of...

Utilization of Improved RBF Network in Modeling of Wave Energy Absorption System

Abstract:

Energy self-supply is one of the most important problems, and there are many undesirable energy difficulties when carrier keeps working underwater, and. A method based on inertial pendulum has been presented, but the model of wave energy absorption efficiency which is a significant parameter is strongly nonlinear and difficult to be gained. A method based on radial basis function (RBF) neural network is adopted to model in time domain. To prevent the problem that structure and parameters of neural network are hard to be tuned, improved RBF network based on particle swarm optimization (PSO) is proposed. The results obtained by presented method and by simulation software ADAMS are compared, which validate the method used to be correct and make basis on future research.

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Applied Mechanics and Materials (Volume 483)

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578-582

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.483.578

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Online since:

December 2013

Authors:

Ying Zhang*, Meng Xin Li, Ran Ran Wang

Keywords:

Adam, Particle Swarm Optimization (PSO), RBF Neural Network, Underwater Carrier, Wave Energy Absorption Efficiency

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