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Earthquake Engineering Problems in Parallel Neuro Environment

机译:并行神经环境中的地震工程问题

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摘要

The aim of the paper is to explore the application of Parallel Neuro Simulator for the generation of artificial earthquake. Parallel Neuro Simulator is a neural network code developed on PARAM 10000 using 'C' language and MPI library subroutines. In this study, two artificial neural network (ANN) models have been proposed to replace the auto-regressive moving average (ARMA) model. First ANN model substitutes the polynomial model that represents the relation of initial site information and coefficients of polynomial and the second ANN based model substitutes the estimated parameters of the ARMA model. Several Indian earthquake records have been used for present study on PARAM 10000. The variation in computational time with increasing number of processors has also been studied.
机译:本文的目的是探索并行神经模拟器在人工地震发生中的应用。并行神经模拟器是使用“ C”语言和MPI库子例程在PARAM 10000上开发的神经网络代码。在这项研究中,已经提出了两种人工神经网络(ANN)模型来代替自回归移动平均(ARMA)模型。第一个ANN模型替代表示初始站点信息与多项式系数之间关系的多项式模型,第二个基于ANN的模型替代ARMA模型的估计参数。印度的几项地震记录已用于当前对PARAM 10000的研究。还研究了随着处理器数量的增加,计算时间的变化。

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