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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: Chen, Haixia; *
Affiliations: Rongzhi College of Chongqing Technology and Business University, Chongqing, China
Correspondence: [*] Corresponding author. Haixia Chen, Rongzhi College of Chongqing Technology and Business University, Chongqing, China. E-mail: chenhaixia190@163.com.
Abstract: Innovation and entrepreneurship are an important support for social and economic development in the new era, and it is also the key to the cultivation of practical talents in universities. In order to mine the effective information of innovation and entrepreneurship data, based on the neural network algorithm, this paper combines the bat algorithm to construct a data processing model to obtain an artificial intelligence innovation and entrepreneurship system with data analysis capabilities. Moreover, this study combines with actual needs to improve the algorithm, effectively eliminate the noise existing in the data, eliminate the interference of invalid data on the judgment ability of the system model, and choose the best denoising algorithm through comparison and verification of various algorithms. In order to verify the model proposed in this paper, the data is input into this research model by collecting data in a college survey, so as to verify and analyze the performance of the model. The research results show that the artificial intelligence system proposed in this paper has good performance and has certain practical value.
Keywords: Artificial intelligence, neural network, improved algorithm, innovation and entrepreneurship
DOI: 10.3233/JIFS-189245
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2517-2528, 2021
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