Research On Prediction Of Sustainable Development Capacity Of Energy Enterprises Based On In-depth Learning

In the past hundred years,human social activities have become more and more frequent,the global climate has also been deteriorating,the temperature has gradually increased,and various extreme weather has occurred frequently,which has seriously affected human survival and development.In this case,China has put forward the goal of achieving carbon peak in 2030 and carbon neutrality in 2060.In the context of this goal,the sustainable development capacity of the energy industry has also received more and more attention.As one of the pillar industries in the national economy,the energy industry’s sustainable development ability is related to the development of China’s economy.Therefore,it is of great significance for the development of the country and enterprises to establish an effective prediction model of sustainable development capacity to predict the sustainable development capacity of enterprises in a timely manner and promote the stable development of enterprises.At the present stage,the research of sustainable development capacity mainly focuses on the use of data analysis,fuzzy comprehensive evaluation,entropy weight TOPSIS and other analysis methods.The research of sustainable development capacity by these methods is still in the post-evaluation stage,but the pre-prediction of sustainable development capacity needs to be realized through in-depth learning.The deep learning model is different from the traditional data analysis method.It can automatically learn the complex relationship features between high-latitude data and feed back the learned features in a way that we can recognize.It is also widely used in various fields because of its ability to process high-dimensional complex data.The purpose of this paper is to apply it to the prediction of the sustainable development ability of enterprises in order to achieve the prediction of the sustainable development ability of the energy industry.Based on the research results of relevant experts at home and abroad,combined with the development characteristics of China’s energy enterprises,this paper constructs a prediction index system for the sustainable development ability of the energy industry from five aspects: economic development,resources and environment,social responsibility,enterprise management and scientific and technological innovation.Finally,the system contains 11 secondary indicators and 30 specific indicators,which comprehensively reflects the sustainable development ability of enterprises.First,select the data of listed energy enterprises in China from 2020 to 2021 as the sample,and apply it to the deep neural network(DNN)algorithm to train and learn the sample features,and obtain a deep learning model that can be applied to the case;Secondly,taking listed coal enterprises in Shanxi Province as an example,the feasibility and applicability of the deep learning model are analyzed,and the performance of the sustainable development ability of coal enterprises in Shanxi Province is analyzed in detail;Finally,based on the analysis results,this paper puts forward corresponding suggestions from the perspective of enterprise’s own development.