Research On Financial Performance Of Leading Enterprises In Agricultural Industrialization Based On Bp Neural Network Model

As the main business carrier to realize the development of agricultural industrialization,leading enterprises in agricultural industrialization have greatly promoted the operation of agricultural industrialization and strongly promoted the high-quality development of China’s agricultural economy.At present,China’s leading enterprises in agricultural industrialization have achieved rapid development with the strong support of national support policies,but there are still many problems in enterprises at this stage,especially the performance evaluation management system of leading enterprises in agricultural industrialization is still insufficient compared with developed countries.Therefore,scientific and reasonable performance evaluation of leading enterprises in agricultural industrialization in China is conducive to promoting the healthy and sustainable development of enterprises and helping to realize the development of agricultural modernization.On the basis of referring to a large number of domestic and foreign related documents and combing the previous scholars’ research,this paper combines the development status,management characteristics and existing problems of leading enterprises in agricultural industrialization in China,and follows the principle of selecting indicators for constructing the evaluation system of financial performance indicators of enterprises,and selects 15 appropriate financial indicators from five dimensions,such as enterprise profitability,debt repayment,operation and development ability and cash flow,to construct the financial performance evaluation system of leading enterprises in agricultural industrialization.This paper selects the financial data of 81 listed leading agricultural industrialization enterprises in Shanghai and Shenzhen stock markets from 2019 to 2021,and constructs a more scientific and reasonable Bp neural network model by constantly adjusting experimental functions and parameters with the help of Matlab R2021 b software.In the process of financial performance evaluation,firstly,the selected financial data from 2019 to 2020 are standardized and used as the input unit of Bp neural network.Secondly,the comprehensive performance value of the enterprise is obtained after the index weight is determined by entropy weight method,and it is used as the expected value of the output unit of Bp neural network;Finally,Bp neural network is used to establish a financial performance evaluation model for training and verification,and the applicability and accuracy of the model are discussed.The evaluation results show that the Bp neural network model constructed in this paper has good applicability and accuracy in the financial performance evaluation of leading enterprises in agricultural industrialization.The overall performance level among leading enterprises in agricultural industrialization is at a low level,the performance level among agricultural enterprises is quite different,and the weights of various indicators in the financial index evaluation system are quite different,among which the accounts receivable turnover rate,inventory turnover rate and cash operation index account for the largest weight.In this regard,this paper puts forward to pay attention to enterprise technology investment and talent training to improve core competitiveness;Establish the internal control system of enterprise accounts receivable,and speed up the information construction of agricultural enterprise inventory;Improve the fund management system of agricultural enterprises and increase the support of government funds.