The Construction of Judgment Model for Cultivating Intelligent Accounting Professionals in Universities Based on Logarithmic Periodic Power Law Model

Abstract

The talent training evaluation model not only helps to evaluate the talent itself but also provides feedback on the content of the talent training evaluation. Therefore, this paper establishes an efficient and intelligent talent training evaluation model for accounting professionals based on the logarithmic cycle power law model. The main content of talent training evaluation is set as general knowledge skills, professional thinking, and values. The log-periodic power-law model and the least squares method are combined to reduce the dimensionality of the nonlinear parameters of the judging content and to quantify the judging of intelligent accounting professional talent training in universities, which is convenient for the calculation of linear functions. With the help of log-periodic power-law oscillation to prove that talent training is changing in a cyclical pattern, the feasibility of its prediction is demonstrated. The study shows that the talent cultivation judgment model constructed based on the log-periodic power-law model is very accurate, especially in talent cultivation value judgment prediction. The model achieves zero error in the prediction of some data, and the maximum error between prediction and actual is only 6%. In the judgment of general knowledge and skill cultivation, the maximum error between the prediction and the actual score of the model is no more than 2 points. This shows that the talent development evaluation model based on the log-periodic power law model can make accurate predictions of talent development evaluation.

Keywords

• log-periodic power law
• least squares
• parametric dimensionality reduction
• log-periodic power law oscillation
• talent development judging model
• 08c99