Comprehensive Analysis and Forecasting of Indicators of Sustainable Development of Nuclear Industry Enterprises
محل انتشار: ماهنامه بین المللی مهندسی، دوره: 38، شماره: 11
سال انتشار: 1404
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 53
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شناسه ملی سند علمی:
JR_IJE-38-11_005
تاریخ نمایه سازی: 26 فروردین 1404
چکیده مقاله:
The study emphasises the key role of nuclear power in ensuring energy security and reducing carbon dioxide emissions, which is in line with global sustainable development requirements. Given its importance for the transition to clean energy, a detailed assessment of environmental, technical, and socio-economic dynamics in the nuclear industry is required. The purpose of the work is to comprehensively analyse and forecast the key indicators of Rosenergoatom Concern OJSC in order to gain insights into the future of the company and the industry.Multivariate analysis, regression modelling, BFGS algorithm and Excel tools were used to identify key trends and influencing factors. The results obtained show positive dynamics in the analysed areas, although some dependencies in the model need to be revised. Nevertheless, the developed methodology is an effective basis for assessing sustainable development, including for other energy companies.The paper develops an approach to the systematization and analysis of indicators of sustainable development of the nuclear industry using integral indicators. It is assumed that the methodology is also applicable for assessing the efficiency of other energy companies. A list of indicators characterizing environmental, technical and socio-economic efficiency has been compiled. In addition, the forecast values of key indicators for the near future have been determined, which demonstrates the practical applicability of the approach.The scientific novelty lies in the combination of multivariate analysis with optimisation techniques, such as BFGS and Solution Finder in Excel, to assess and predict the sustainable development of the nuclear industry.
کلیدواژه ها:
نویسندگان
O. A. Marinina
Department of Industrial Economincs, Saint Petersburg Mining University, Saint Petersburg, Russia
Y. V. Ilyushin
System Analysis and Control Department, Saint Petersburg Mining University, Saint Petersburg, Russia
E. V. Kildiushov
Department of Industrial Economincs, Saint Petersburg Mining University, Saint Petersburg, Russia
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