Research On The Accounting Of Natural Resources Assets And Liabilities Based On Intelligent Computing

With the continuous intensification of the conflict between man and nature,the over-exploitation of natural resources,waste of resources and other issues have attracted more and more attention.The environmental accounting system has been incorporated into the national accounting accounts,and the accounting of natural resources has received great attention.In order to find out the problems of difficult data collection,difficult value quantification,inaccurate comprehensive evaluation,and low concept of sustainable development in the outgoing audit of leading cadres of natural resources,this paper takes the preparation of natural resources balance sheets as the main line to expand Research on the accounting of natural resource assets and liabilities.This paper has carried out theoretical research work including the theory and practice of natural resources assets and liabilities,the application of intelligent computing methods,and systematic comprehensive evaluation.By comparing the account indicators of the main environmental accounting systems at home and abroad,a general and applicable natural resource asset and liability accounting system is established,and the "total-score" structure of the natural resource liability statement is determined.Land,minerals and water resources are three main resources.A physical asset account,an asset value account and a liability account have been established.The accounting system includes the evaluation of assets and liabilities and comprehensive evaluation of statements,and has preliminarily determined the evaluation and evaluation model methods of natural resources assets and liabilities.And in the aspect of natural resource value accounting,the BP algorithm was introduced,and the algorithm was optimized by adaptive weight and improved on the whale optimization algorithm,and a value evaluation model of the adaptive whale optimization BP neural network(IWOA-BP)was constructed.The data is used for model training and testing,and the results of traditional BP,WOA-BP and PSO-BP are compared,which shows the feasibility and effectiveness of the method.In terms of case analysis,taking Yulin City as an example,the physical quantity of natural resources is directly filled in,and the asset value account and liability account are filled in after calculation using a model combining traditional methods and intelligent calculation methods,so as to summarize Trial compilation of Yulin City’s land,mineral and water resources balance sheet,first classification and then synthesis,from bottom to top formed a general statement of Yulin City’s natural resources assets and liabilities,and carried out a comprehensive evaluation and analysis of the statement.Through case analysis,this study has the following main conclusions:(1)For the accounting of land,minerals and water resources in Yulin City,the total value of natural resources assets in Yulin City is 60227.072 billion yuan,the total liability is 21.855 billion yuan,and the value of mineral resources accounts for 60227.072 billion yuan.than the highest.(2)The overall assessment of the social-ecological system in Yulin City was carried out,and the calculation result of the degree of coupling and coordination was good,indicating that there is a good mutual benefit and symbiosis between the social and economic development of Yulin City and the ecology.(3)Adaptive whale optimization The improved BP neural network algorithm has better solution advantages than other optimization algorithms in the evaluation of natural resources value in this paper.To sum up,this article runs through the whole text by compiling the natural resource balance sheet,carries out the assessment of natural resource assets and liabilities and the comprehensive evaluation of the statement,carries out theoretical research,construction of accounting system,combination of intelligent calculation methods and case analysis,through the whale optimization algorithm.The intelligent calculation methods such as BP neural network and BP neural network were explored and applied with water resources as an example,and combined with traditional methods,the overall natural resource asset and liability statement was trial compiled and analyzed.Finally,the paper summarizes and analyzes the shortcomings,provides suggestions,and discusses the future prospects of the current research,in order to provide some reference for the evaluation of natural resources in Shaanxi Province.