The Platform Of Enterprise Value Prediction And Information Management Based On Random Forest Algorithm

As information technology advances rapidly,more and more companies have emerged in the industry to carry out intelligent management to improve the quality and accuracy of projects.At present,the high-tech park where I work still uses manual methods to prepare materials according to the actual needs of software information companies.This method is not only inefficient,but also not accurate;It also only relies on the self-introduction of the enterprise,and judges and predicts the enterprise in a subjective way which is lacking the objectivity supported by data.Therefore,this paper designs an enterprise value forecasting and information management platform.It can import software information enterprises’ data according to the actual needs of the enterprise,automatically generate corresponding industrial and commercial,taxation and other materials,and predict enterprise value based on the enterprise’s debt repayment,profit,operation,development,taxation and other data.This platform would help to provide enterprises with better relevant support policies of the park.The primary areas of research include:(1)Analyze and determine the functions and business processes of the enterprise value forecast and information management platform.The corresponding use case diagram of the platform and the timing analysis of system functions are given,and the specific functional requirements and non-functional requirements of the platform’s main interface module,certificate management module,enterprise information management module,tax management module and enterprise value forecast module are described.(2)Build an enterprise value prediction model based on the random forest algorithm.Carry out data preprocessing on corporate reports,and analyze the debt repayment ability statement,operating benefit statement,profitability statement,development potential statement,cash flow indicator statement,and corporate tax statement,which mainly include corporate value-added tax,corporate income tax,and personal income tax information.The Gini is employed to choose the most favorable eigenvalue.The SVR method is used for model training,and the Python language is used for model implementation.Finally the final prediction result of the model is given.(3)Based on the front-end and back-end separation mode,the functions of enterprise value prediction and information management platform are implemented.Design the system architecture and logical structure of the system,give the specific operation interface of the platform’s certificate management module,enterprise information management module,tax management module and enterprise value prediction module functions,and give the corresponding platform function user process and test example.The enterprise value prediction and information management platform based on the random forest algorithm can enable the park enterprise service personnel to save repetitive operations,prepare materials more efficiently and accurately and predict enterprise value more objectively,improve work efficiency and generate greater profits Enterprise and park benefits.