Abstract
As the global economy continues to grow, the business scope of enterprises is further expanded, the environment will become more complex, the risks they face will increase, and the uncertainty will gradually increase. If an enterprise fails to manage risks properly, it will not only affect the normal operation of the enterprise, but may even lead to bankruptcy. This paper aims to study the risk prediction and processing in enterprise management based on the ant colony parallel algorithm. Based on the analysis of the current situation of risk prediction research at home and abroad, combined with the function of risk prediction and the principle of risk prediction index selection, a risk prediction system is established and reused. The parallel and distributed characteristics of ant colony algorithm establish a risk prediction model to predict enterprise management risks. The prediction results show that the relative error value of all samples is controlled below 3%, and the minimum error value is only 0.86%. Therefore, the ant parallel algorithm model can meet the accuracy requirements of enterprise management risk prediction.
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Shi, K. (2022). Risk Prediction and Treatment in Enterprise Management Based on Ant Colony Parallel Algorithm. In: Al-Turjman, F., Rasheed, J. (eds) Forthcoming Networks and Sustainability in the IoT Era. FoNeS-IoT 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 129. Springer, Cham. https://doi.org/10.1007/978-3-030-99616-1_14
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DOI: https://doi.org/10.1007/978-3-030-99616-1_14
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