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Issue title: Complex evolutionary artificial intelligence in cognitive digital twinning
Guest editors: Neal Wagner, Sundhararajan, Le Hoang Son and Meng Joo
Article type: Research Article
Authors: Wenjuan, Zhang; *
Affiliations: International Education Department, Inner Mongolia Business & Trade Vocational College, Hohhot, Inner Mongolia, China
Correspondence: [*] Corresponding author. Zhang Wenjuan, Inner Mongolia Business & Trade Vocational College, E-mail: fhzhahy77@sina.com.
Abstract: The traditional English examination and the current examination system have been unable to meet the needs of the education industry for English examinations. In view of this, based on the neural network algorithm, this study proposes a hierarchical network management model from the user’s perspective. Based on the in-depth study of the neural network, this study combined with the network performance characteristics of large data volume, complex data to propose a new BP neural network algorithm. By dynamically changing the momentum factor and learning rate, the algorithm has greatly improved the accuracy and stability of the error. In addition, this study proposes a user perception prediction model, and the model is continuously trained on the model based on the improved BP neural network algorithm and the monitored network performance. In order to study the performance of the research model, a control experiment is designed to analyze the performance of the model. The research results show that the intelligent model and algorithm proposed in this paper are completely feasible and effective.
Keywords: Neural network, English, hierarchical model, improved algorithm
DOI: 10.3233/JIFS-189241
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2469-2480, 2021
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