Data assimilation by cellular neural network applied to Lorenz-63 system

IF 3.7 3区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Computational Science Pub Date : 2025-05-30 DOI:10.1016/j.jocs.2025.102587

César Magno Leite de Oliveira Júnior , Antonio Mauro Saraiva , Alexandre Cláudio Botazzo Delbem , Haroldo Fraga de Campos Velho , Gerônimo Gallarreta Zubiaurre Lemos , Fabrício Pereira Härter

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引用次数: 0

Abstract

Data assimilation is an important process to compute the best initial condition for a computational prediction system, combining a previous prediction (background) with observation. The result from this procedure is the computed analysis. A cellular neural network (Cell-NN) is applied as a data assimilation (DA) method. The Cell-NN is also employed to integrate dynamic systems in time. Different Cell-NN configurations are developed for the DA process and as an integration scheme. The Lorenz system under a chaotic dynamical regime is used for testing with Cell-NN. Data assimilation with the 3D variational (3D-Var) method is also implemented for comparison. Cell-NN belongs to the class of unsupervised neural networks. The performance for computing the analysis by Cell-NN presented a similar error magnitude to the 3D-Var technique.

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细胞神经网络数据同化在Lorenz-63系统中的应用

数据同化是计算预测系统计算最佳初始条件的一个重要过程，它将先前的预测（背景）与观测相结合。这个过程的结果就是计算分析。采用细胞神经网络（Cell-NN）作为数据同化（DA）方法。利用Cell-NN对动态系统进行实时集成。不同的Cell-NN配置被开发用于数据处理和作为一种集成方案。利用混沌动力状态下的洛伦兹系统对Cell-NN进行了测试。用三维变分（3D- var）方法同化数据进行比较。Cell-NN属于无监督神经网络。Cell-NN计算分析的性能与3D-Var技术具有相似的误差幅度。

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来源期刊

Journal of Computational Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

5.50

自引率

3.00%

发文量

227

审稿时长

41 days

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