Abstract
With the rapid development of information technology, more and more people use social networks to express their opinions. Therefore, it is of great significance to establish appropriate model for prediction of information dissemination. Because the physical meaning of the fractional model is clearer, its expression is simpler, therefore, the fractional SEIRS model based on the conformable derivative is introduced in this study, which is more matches the true situation. Taking the forwarding amount of the eighth question of the 2018 college entrance examination as an example, the fractional SEIRS model is used for data fitting. And the results show that the model fitting curve is basically consistent with the real data curve, the SEIRS model in this study has an important guiding role in predicting the trend of information dissemination.
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Acknowledgments
Construction of Special Funds for Key Disciplines in Shaanxi Universities, Science Foundation of the Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing, the Natural Science Foundation of Shaanxi Province (2018JM1055). National Civil Affairs Commission National Research Project (2018-GME-010), Shaanxi Province Key Research and Development Program (2018GY-150), Xi’an Science and Technology Plan Project (201805040YD18CG24-3), Shaanxi Province Key Laboratory of Network Data Analysis and Intelligent Processing (XUPT-KLND (201806)).
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Tong, Q., Wang, H., Zhang, J., Li, L., Huang, Q. (2020). The Fractional SEIRS Epidemic Model for Information Dissemination in Social Networks. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1075. Springer, Cham. https://doi.org/10.1007/978-3-030-32591-6_30
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DOI: https://doi.org/10.1007/978-3-030-32591-6_30
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