Application of Numerical Deconstruction in Enterprise Economic Management
Lipeng Wang and
Sagheer Abbas
Mathematical Problems in Engineering, 2022, vol. 2022, 1-9
Abstract:
The rapid development of the global economy has provided new opportunities for all walks of life and enabled enterprises to develop in an all-round way. Under the multi-faceted competition, enterprises need to improve their comprehensive capabilities, so they need to effectively manage the enterprise economy in the process of enterprise operation. The traditional enterprise economic management model mainly predicts the future enterprise economy by analyzing the enterprise economic status of the previous period, but there are defects such as poor prediction accuracy and low management efficiency. Numerical analysis is the analysis and processing of numerical problems through techniques such as computers. By comparing with traditional management methods, numerical analysis is applied to enterprise economic management. The experimental results show that in terms of employee technical training time and reward innovation, the accuracy of enterprise economic forecasting under the binary regression method is 98%, and the accuracy under the univariate regression method is 61.7%. And the economic benefit brought by the optimal solution under the binary regression analysis is 45.8% higher than that of the single regression method, and the economic management efficiency of the enterprise is 23.5% higher. In terms of enterprise cost input and employee distribution, the method of binary regression applied to enterprise economic management is superior to the univariate regression method in terms of the accuracy of enterprise economic forecasting, the economic benefits, and the efficiency of enterprise economic management. Therefore, the application of numerical analysis in enterprise economic management can predict the development trend of the enterprise economy, ensure the economic benefits of the enterprise, and improve the management efficiency of the enterprise economy.
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:2846062
DOI: 10.1155/2022/2846062
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