Research On The Assets Quality Evaluation Of Robam Based On BP Neural Network

Assets as the material foundation on which enterprises depend are the material guarantee for enterprises to win competition in the market.With the development of the times,the connotation of assets is becoming richer and richer,and it needs to be evaluated in a more novel angle and way.The importance of asset quality is beginning to increase.The home appliance industry itself has the characteristics of large fixed asset investment and fast product replacement,etc.making asset quality of great significance to home appliance companies.As a veteran household appliance enterprise,Robam has shown a downward trend in profitability,growth ability,and stock price in recent years.This article uses the Back Propagation neural network to build an asset quality evaluation model,objectively evaluate the asset quality of the home appliance industry and the Robam,and explore the reasons for the changes in the asset quality of the Robam.It is hoped that it can provide ideas for optimizing asset quality evaluation methods and bring convenience to investment object selection and asset management.First of all,based on the research results of scholars,this article determines the asset quality evaluation index system suitable for the household appliance industry;then select 30 sample companies,calculate and normalize their asset quality evaluation indicators from 2014 to 2018,and obtain the input data needed to establish the model;subsequently,the entropy weight method was used to score and grade the asset quality of the sample enterprises to obtain the expected output value required for training the neural network;then use the obtained data to train and simulate the Back Propagation neural network.The results show that the establishment of the asset quality evaluation model is successful,and it can be used in practical applications.Then the financial data of the Robam are input into the model to objectively evaluate its asset quality.The output results show that the company's asset quality is declining year by year.In order to find the problems in its asset management,the traditional financial analysis method is used to analyze the various indicators of enterprise asset quality.This article mainly draws the following conclusions through research: first,asset turnover quality plays an important role in asset quality evaluation,and companies in particular need to pay attention to increasing the receivable turnover rate;second,the asset quality evaluation model based on Back Propagation neural network is successful and it has the advantages of fastness,objectivity,integrity and convenience compared with traditional financial analysis methods,so it can bring a lot of convenience to managers and investors;third,the low inventory turnover rate of Robam has formed a vicious circle,which has adversely affected the profitability and structural quality of assets.