Dynamic Modeling Approach Based on Improved PSO and FLANN for Sensor

Zhang YuanYuan;Xu KeJun;Xu Yaohua

Journal of Vibration and Shock ›› 2009, Vol. 28 ›› Issue (1) : 1-3.

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PDF(835 KB)
Journal of Vibration and Shock ›› 2009, Vol. 28 ›› Issue (1) : 1-3.
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Dynamic Modeling Approach Based on Improved PSO and FLANN for Sensor

  • Zhang YuanYuan1,2,Xu KeJun3,4,Xu Yaohua2
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Abstract

In this paper, the dynamic linear model of sensor is founded based on the improved particle swarm optimization (PSO) algorithm and function link artificial neural network (FLANN). According to measurement data in dynamic calibration ,the weights of network is used to initialize one particle station of whole particel swarm when the training of FLANN has finished.Then the improved PSO algorithm is applied ,the global best particle station of particle swarm is the coefficient of sensor’s dynamic model what we need. The experiment results show that this approach has excellence of both PSO and FLANN, meanwhile it has better precision.

Key words

mass air flux sensor / particle swarm optimization / function link artificial neural network(FLANN) / modeling

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Zhang YuanYuan;Xu KeJun;Xu Yaohua. Dynamic Modeling Approach Based on Improved PSO and FLANN for Sensor [J]. Journal of Vibration and Shock, 2009, 28(1): 1-3
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