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Research on Gaussian Calculation Simulation Reaction Model based on Computer Big Data

Published: 26 October 2022 Publication History

Abstract

In order to meet the real-time requirements of the online modeling algorithm, the adaptive natural gradient method (ANG) is proposed in the training of the Gaussian process, which is an online Gaussian process regression modeling algorithm based on the adaptive natural gradient method. This paper proposes an effective learning algorithm of Gaussian mixture model. Using this algorithm to process simulated video data and real video, the results show that the learning algorithm proposed in this paper is superior to the previous methods in terms of convergence rate and accuracy.

References

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Zhang Wei, Ying Zuguang. Gaussian correlation process simulation of random dynamic response. Noise and Vibration Control, vol. 39, pp.4-18, March 2019.
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Pan Xinkai, Wang Xiaodun, Zhu Haitao. Three-dimensional Path Integration Analysis of the Nonlinear Response of Simply Supported Beams. Chinese Journal of Computational Mechanics, vol. 36, pp.6-22, March 2019.
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PAN Xin-kai, WANG Xiao-dun, ZHU Hai-tao. Analysis of the nonlinear response of simply supported beams by three-dimensional path integration method. Chinese Journal of Computational Mechanics, vol. 36, pp.395-400, March 2019.
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Feng Zebiao, Wang Jianjun, Ma Yizhong. Bayesian modeling and robust parameter design based on multivariate Gaussian process model. System Engineering Theory and Practice, vol. 40, pp.11-29, March 2020.
[5]
Liu Chenhui. Calculation of roughness uncertainty based on Gaussian filtering. Journal of Tianjin University of Technology, vol. 11, pp.5-18, February 2019.
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Shi Xue, Li Yu, Zhao Quanhua. Hierarchical Gaussian Mixture Model and M-H Remote Sensing Image Segmentation Algorithm. Journal of China University of Mining and Technology, vol. 48, pp.8-19, March 2019.
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Xie Yushan, Huang Yi, Zhong Yujie, Terahertz measurement method of liquid electromagnetic parameters based on Gaussian mixture model. Applied Optics, vol. 42, pp.1-7, June 2021.
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Shen Yu, Liu Cheng, Yang Qian. Super-resolution image reconstruction algorithm using subspace sparse features. Computer Engineering and Applications, vol. 57, pp. 10-20, May 2021.

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  1. Research on Gaussian Calculation Simulation Reaction Model based on Computer Big Data

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    ICCSIE '22: Proceedings of the 7th International Conference on Cyber Security and Information Engineering
    September 2022
    1094 pages
    ISBN:9781450397414
    DOI:10.1145/3558819
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 26 October 2022

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