Abstract
In the process of complex network modeling training, when the uncertainty relation is used to judge whether the overfitting phenomenon occurs, the overfitting parameters in the discriminant are too large to be determined, which greatly limits the role of the discriminant in guiding the modeling process of complex network. The purpose of this paper is to provide technical advice for rapid network fitting through the research on the method of rapid network fitting based on deep learning (DL). This paper proposes a fast network fitting method based on DL. Simulation results show that the speed of this method is 21.67% higher than that of the traditional algorithm, which proves that this method is feasible.
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Li, M., Huang, Z. (2021). Fast Fitting Method of Complex Network Based on Deep Learning. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2020. Advances in Intelligent Systems and Computing, vol 1303. Springer, Singapore. https://doi.org/10.1007/978-981-33-4572-0_138
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DOI: https://doi.org/10.1007/978-981-33-4572-0_138
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