Title: An enterprise financial data risk prediction model based on entropy weight method

Authors: Wenyuan Chen

Addresses: Accounting School, Jiangsu Vocational Institute of Economic and Trade Technology, Nanjing 211168, China

Abstract: The traditional financial risk prediction model has some problems, such as inaccurate prediction results due to the poor selection of risk index system. This paper proposes to build an enterprise financial data risk prediction model based on entropy weight method. The enterprise risk financial data prediction index system is built and the prediction index is obtained. The entropy weight method is used to calculate the weight of prediction index and to obtain the weight coefficient. The data with higher risk index weight is input into the neural network as the initial vector of prediction, the weight of risk data nodes at different levels of the network is calculated, the risk prediction model is constructed, and the error of the output solution of the model is corrected by the incentive function to realise the risk prediction. The experimental results show that the prediction accuracy of the model is always about 98%.

Keywords: entropy method; enterprise financial risk; index system; weight; predictive model.

DOI: 10.1504/IJISE.2023.133533

International Journal of Industrial and Systems Engineering, 2023 Vol.45 No.1, pp.89 - 100

Received: 06 Aug 2021
Accepted: 18 Dec 2021
Published online: 19 Sep 2023 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article