Research article

Fuzzy-Logical model for analysis of sustainable development of fuel and energy complex enterprises

  • Received: 22 May 2023 Revised: 15 August 2023 Accepted: 28 August 2023 Published: 12 October 2023
  • The purpose of this article is to build a mathematical model for analyzing the sustainability of the development of an enterprise in the fuel and energy complex, integrated into an information management system. It is noted that one of the strategic dominants in achieving the national goal of accelerating the technological development of any country is to ensure the effective functioning of enterprises in the fuel and energy complex. It is substantiated that these enterprises represent the basis of the material life of society, thus, ensuring their sustainable development is a significant factor for the formation of the structure of sectoral and inter-sectoral industrial complexes. In order to analyze the sustainable development of enterprises, an integral indicator is proposed, the components of which are the vectors of production, organizational, economic, environmental and social characteristics. Due to the weak structure of some characteristics, to solve the problem of their synthesis with quantitatively defined indicators, it is proposed to use the mathematical apparatus of fuzzy logic. Weakly structured indicators are formally described by linguistic variables. To establish the dependence of the integral indicator of sustainable development on production, organizational, economic, environmental and social indicators, a fuzzy-logical model has been built, which makes it possible to use the knowledge of experts by constructing rules of fuzzy inference. The fuzzy logic model is implemented using MATLAB tools. On the constructed model, experiments were carried out to assess the impact of each of the local indicators of sustainable development of an enterprise on the integral indicator. The advantage of the constructed model is its adaptability to changes in the operating conditions of enterprises.

    Citation: Alex Borodin, Elena Streltsova, Zahid Mamedov, Irina Yakovenko, Irina Mityshina, Artem Streltsov. Fuzzy-Logical model for analysis of sustainable development of fuel and energy complex enterprises[J]. AIMS Energy, 2023, 11(5): 974-990. doi: 10.3934/energy.2023046

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  • The purpose of this article is to build a mathematical model for analyzing the sustainability of the development of an enterprise in the fuel and energy complex, integrated into an information management system. It is noted that one of the strategic dominants in achieving the national goal of accelerating the technological development of any country is to ensure the effective functioning of enterprises in the fuel and energy complex. It is substantiated that these enterprises represent the basis of the material life of society, thus, ensuring their sustainable development is a significant factor for the formation of the structure of sectoral and inter-sectoral industrial complexes. In order to analyze the sustainable development of enterprises, an integral indicator is proposed, the components of which are the vectors of production, organizational, economic, environmental and social characteristics. Due to the weak structure of some characteristics, to solve the problem of their synthesis with quantitatively defined indicators, it is proposed to use the mathematical apparatus of fuzzy logic. Weakly structured indicators are formally described by linguistic variables. To establish the dependence of the integral indicator of sustainable development on production, organizational, economic, environmental and social indicators, a fuzzy-logical model has been built, which makes it possible to use the knowledge of experts by constructing rules of fuzzy inference. The fuzzy logic model is implemented using MATLAB tools. On the constructed model, experiments were carried out to assess the impact of each of the local indicators of sustainable development of an enterprise on the integral indicator. The advantage of the constructed model is its adaptability to changes in the operating conditions of enterprises.



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