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Research on early warning algorithm for economic management based on Lagrangian fractional calculus

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  • Su, Xin
  • Yu, Keshu
  • Yu, Miao

Abstract

The occurrence of economic management crisis has seriously affected the production and operation of enterprises, the stability of capital markets and even the economic security of the entire country and the world. The use of higher mathematics in economic management is very beneficial to the economic restructuring. For example, in the Lagrangian method for solving the constraint optimization problem, the correlation function can be listed in the Lagrangian fractional calculus equation for the economic management early warning problem with many independent variables. Then take one of the factors as the dependent variable and other factors as fixed constants, and bring them into the Lagrangian fractional calculus equation, you can find the variable solution and get the extreme value of the economic management early warning algorithm. Therefore, this paper combines normative research and empirical research to study the algorithm design, theoretical analysis and numerical experiments of Lagrangian-based methods for solving constrained optimization problems. The Lagrangian fractional calculus method is used to evaluate the early warning algorithm of economic management, improve the prediction accuracy and practicability of the model, and conduct empirical research. It is expected to find a way to effectively determine whether a listed company is caught in an economic management crisis and provide early warning for the listed company's own management.

Suggested Citation

  • Su, Xin & Yu, Keshu & Yu, Miao, 2019. "Research on early warning algorithm for economic management based on Lagrangian fractional calculus," Chaos, Solitons & Fractals, Elsevier, vol. 128(C), pages 44-50.
    • Handle: RePEc:eee:chsofr:v:128:y:2019:i:c:p:44-50
    DOI: 10.1016/j.chaos.2019.06.020
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    References listed on IDEAS

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    1. Yu, Miao & Song, Jinguo, 2018. "Volatility forecasting: Global economic policy uncertainty and regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 316-323.
    2. Xinglong Yuan & Wenbing Chang & Shenghan Zhou & Yang Cheng, 2018. "Sequential Pattern Mining Algorithm Based on Text Data: Taking the Fault Text Records as an Example," Sustainability, MDPI, vol. 10(11), pages 1-19, November.
    3. Jumarie, Guy, 2007. "Lagrangian mechanics of fractional order, Hamilton–Jacobi fractional PDE and Taylor’s series of nondifferentiable functions," Chaos, Solitons & Fractals, Elsevier, vol. 32(3), pages 969-987.
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