Prediction of Dynamic Deformation Monitoring Based on IGA Artificial Neural Network Model

Yu Zhu; Qing Zhao

doi:10.4028/www.scientific.net/AMM.204-208.4760

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The Properties of Case-Weight Model when the Row and Column of Design Matrix Simultaneous Mitted
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 204-208Prediction of Dynamic Deformation Monitoring Based...

Prediction of Dynamic Deformation Monitoring Based on IGA Artificial Neural Network Model

Abstract:

Dynamic deformation data analysis and prediction is a complex systematic project. Aimed at the shortcoming of the traditional prediction model, a method to design the BP neural network based on Immune Genetic Algorithm(IGA) was proposed. The mechanisms of diversity maintaining and antibody density regulation exhibited in a biological immune system were introduced into IGA based on genetic algorithm. The proposed algorithm overcame the problems of GA on search efficiency, individual diversity and prematur, and enhanced the convergent performance effectively. The results show that the BP neural network designed by IGA have better performance in convergent speed and global convergence, and the forecasting accuracy is improved, which illustrates IGA-BP neural network has certain of value on dynamic deformation monitoring forecasting.

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Periodical:

Applied Mechanics and Materials (Volumes 204-208)

Pages:

4760-4765

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.204-208.4760

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Online since:

October 2012

Authors:

Yu Zhu, Qing Zhao

Keywords:

Antibody Encoding, Bp Neural Network Model, Dynamic Deformation Monitoring, Immune Genetic Algorithm (IGA)

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