Published November 2019 | Version v1
Journal article

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

  • 1. School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing (China)
  • 2. Business School, China University of Political Science and Law, Beijing (China)

Description

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.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.chaos.2019.06.020

Additional details

Identifiers

DOI
10.1016/j.chaos.2019.06.020;
PII
S0960077919302322;

Publishing Information

Journal Title
Chaos, Solitons and Fractals
Journal Volume
128
Journal Page Range
p. 44-50
ISSN
0960-0779

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54120622
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING;
Descriptors DEI
ALGORITHMS; CORRELATION FUNCTIONS; LAGRANGIAN FUNCTION; MATHEMATICS; OPERATION; OPTIMIZATION
Descriptors DEC
FUNCTIONS; MATHEMATICAL LOGIC

Optional Information

Copyright
Copyright (c) 2019 Elsevier Ltd. All rights reserved.