Management of the natural resource potential of the Perm region on the basis of a second-order finite-difference model

The article is devoted to the problem of natural resource potential management based on a finite-difference model of the 2nd order. In previous studies, it was found that the management of natural resource potential using finite-difference models allows us to obtain qualitative forecasts in comparis...

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Veröffentlicht in:Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics Automatic Control & Radioelectronics, 2022-04, Vol.22 (2), p.96-106
Hauptverfasser: Zatonskiy, Andrey V., Sirotina, Natalia A.
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container_title Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics
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Sirotina, Natalia A.
description The article is devoted to the problem of natural resource potential management based on a finite-difference model of the 2nd order. In previous studies, it was found that the management of natural resource potential using finite-difference models allows us to obtain qualitative forecasts in comparison with the traditionally used linear multiple models. Purpose of work. The purpose of this work is to build a finite-difference model of a complex indicator of the second-order natural resource potential based on statistical data and to evaluate its predictive properties on the example of the Perm Region. Materials and methods. The second-order finite-difference model was obtained by adding autoregressive terms of the first and second orders to the multiple linear regression model. Based on trends, a forecast of factors was made and the corresponding model values were calculated. The ability to control the factors determining the PRP was established on the basis of their qualitative analysis. Estimates of the impact of changes in factors on the level of PRP were made by increasing and decreasing the forecast values of the selected controlled and uncontrolled factors by 5%. A system of recommendations for the regional government on the management of the natural resource potential of the Perm Region for 2019 and 2020 has been developed. The results of the study. It was revealed that during both forecast periods, the negative dynamics of the PRP as a result of a decrease in uncontrolled factors – a decrease of 0.01 in 2019. and by 0.02 in 2020. it is compensated by its positive dynamics as a result of the growth of controlled factors – an increase of 0.15 in 2019 and 0.16 in 2020. Since an increase in controlled factors by 5% allows for a significant increase in PRP, an increase in controlled factors by less than 5% is sufficient to compensate for the negative impact of unmanaged factors. Discussion and conclusion. The results obtained allow us to assert that the use of a second-order finite-difference model makes it possible to effectively manage the level of the natural resource potential of the region.
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In previous studies, it was found that the management of natural resource potential using finite-difference models allows us to obtain qualitative forecasts in comparison with the traditionally used linear multiple models. Purpose of work. The purpose of this work is to build a finite-difference model of a complex indicator of the second-order natural resource potential based on statistical data and to evaluate its predictive properties on the example of the Perm Region. Materials and methods. The second-order finite-difference model was obtained by adding autoregressive terms of the first and second orders to the multiple linear regression model. Based on trends, a forecast of factors was made and the corresponding model values were calculated. The ability to control the factors determining the PRP was established on the basis of their qualitative analysis. Estimates of the impact of changes in factors on the level of PRP were made by increasing and decreasing the forecast values of the selected controlled and uncontrolled factors by 5%. A system of recommendations for the regional government on the management of the natural resource potential of the Perm Region for 2019 and 2020 has been developed. The results of the study. It was revealed that during both forecast periods, the negative dynamics of the PRP as a result of a decrease in uncontrolled factors – a decrease of 0.01 in 2019. and by 0.02 in 2020. it is compensated by its positive dynamics as a result of the growth of controlled factors – an increase of 0.15 in 2019 and 0.16 in 2020. Since an increase in controlled factors by 5% allows for a significant increase in PRP, an increase in controlled factors by less than 5% is sufficient to compensate for the negative impact of unmanaged factors. Discussion and conclusion. 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The ability to control the factors determining the PRP was established on the basis of their qualitative analysis. Estimates of the impact of changes in factors on the level of PRP were made by increasing and decreasing the forecast values of the selected controlled and uncontrolled factors by 5%. A system of recommendations for the regional government on the management of the natural resource potential of the Perm Region for 2019 and 2020 has been developed. The results of the study. It was revealed that during both forecast periods, the negative dynamics of the PRP as a result of a decrease in uncontrolled factors – a decrease of 0.01 in 2019. and by 0.02 in 2020. it is compensated by its positive dynamics as a result of the growth of controlled factors – an increase of 0.15 in 2019 and 0.16 in 2020. 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Estimates of the impact of changes in factors on the level of PRP were made by increasing and decreasing the forecast values of the selected controlled and uncontrolled factors by 5%. A system of recommendations for the regional government on the management of the natural resource potential of the Perm Region for 2019 and 2020 has been developed. The results of the study. It was revealed that during both forecast periods, the negative dynamics of the PRP as a result of a decrease in uncontrolled factors – a decrease of 0.01 in 2019. and by 0.02 in 2020. it is compensated by its positive dynamics as a result of the growth of controlled factors – an increase of 0.15 in 2019 and 0.16 in 2020. Since an increase in controlled factors by 5% allows for a significant increase in PRP, an increase in controlled factors by less than 5% is sufficient to compensate for the negative impact of unmanaged factors. Discussion and conclusion. 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title Management of the natural resource potential of the Perm region on the basis of a second-order finite-difference model
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