Statistical analysis and forecasting of extraction and use of natural resources

Tärasyev, A.M.; Vasilev, Julian; Turygina, Victoria F.

doi:10.1063/1.5079109

Cited by 7 publications

(3 citation statements)

References 3 publications

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“…NR represents the natural wealth of a country or region include of minerals, petroleum, natural gas, coal, metals, stone, sand, air, sunlight, forests, land, and water. In papers George and Schillebeeckx [5] and George et al [6] are given of the management of NR and in papers Nelson et al [7], Smith [8], Tarasyev et al [9], and Tarasyev et al [10] are given of statistical analysis of different NR.…”

Section: Introductionmentioning

confidence: 99%

Trend Analysis of Total Affected Water and Total Discharged Wastewater of Nišava District (Serbia)

Pavićević

2020

Open Access Maced J Med Sci

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BACKGROUND: Water, as a natural resource, is the most basic substance of life that has immeasurable significance for the living world, ecosystems, and planet Earth. It is consumed by plants, animals, and humans. AIM: We aimed to preform a trend analysis of total affected quantities of water and total discharged wastewater (TDWW) of Nišava district (Serbia). METHODS: In this paper, a trend analysis is given of total affected quantities of water, delivered quantities of drinking water (DQDW), total discharged wastewater (TDWW), wastewater discharges to wastewater systems, and number of households connected to the water supply network of Nišava district (Serbia). RESULTS: The values for Nišava district (Serbia) for total affected quantities of water and DQDW for the period 2006–2018 and wastewater discharges to wastewater systems for the period 2009–2018 decreased, whereas the values for Nišava district (Serbia) for TDWW for the period 2006–2018 and number of households connected to the water supply network for the period 2007–2018 increased. The paper also provides regression models for approximation DQDW (eq. 1) and TDWW (eq. 2) for Nišava district (Serbia) for the period 2006–2018. CONCLUSION: Values for total affected quantities of water (×103 m³) for Nišava district (Serbia) for the period 2006–2018, they decreased from 41740 in 2006 to 9931 in 2018.

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Section: Introductionmentioning

confidence: 99%

Trend Analysis of Total Affected Water and Total Discharged Wastewater of Nišava District (Serbia)

Pavićević

2020

Open Access Maced J Med Sci

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“…Natural resources (NR) are raw organic materials or substances, found in nature and representing the general natural wealth with its usable value for industrial production and/or consumption [1], [2], [3], [4], [5]. Statistical analysis of different NR is given in papers [6], [7], [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Delivered Quantities of Drinking Water and Discharged Wastewater of the Nišava District (Serbia)

Pavićević

2020

Open Access Maced J Med Sci

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Water, as a natural resource, is the most basic substance of life that has immeasurable significance for the living world, ecosystems, and planet earth. In this paper, a prediction of delivered quantities of drinking water (DQDW) and total discharged wastewater (TDWW) of the Nišava district (Serbia) for the period 2019-2023 is given. The prediction for DQDW for the period 2019-2023 was made based on linear regression model, quadratic regression model, and cubic regression model according to which the data on DQDW of the Nišava district (Serbia) for the period 2006-2018 were approximated. The prediction for TDWW for the period 2019–2023 was done based on the 4th-degree polynomial regression model, the 5th-degree polynomial regression model, and the 6th-degree polynomial regression model by which the DQDW data were approximated of the Nišava district (Serbia) for the period 2006–2018. The presented prediction is a continuation of the paper “Trend analysis of total affected water and total discharged wastewater of the Nišava district (Serbia)” by the same author, in which for data on DQDW and TDWW of the Nišava district (Serbia) for the period 2006–2018 trend analysis and selected regression models have been shown.

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“…Various statistical methods can be used to analyze experimental data obtained in environmental research as well as in social and economic sciences [8][9][10][11][12][13][14][15]. This article presents the results of cluster analysis of the chemical composition of samples of agricultural vegetation, collected in the vicinity of the copper-pyrite ore deposit.…”

Section: Introductionmentioning

confidence: 99%

On the application of cluster analysis for vegetation pollution assessment in the area of mining enterprise

Медведев

Melnichenka

2019

Proceedings of the 45th International Conference on Application of Mathematics in Engineering and Economics (Amee’19)

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The assessment of vegetation contamination in the influence area of mining enterprises is an important part of the research during the environment monitoring. There are different statistical methods that can be used for the analysis of data obtained in environmental monitoring. The article presents the results of cluster analysis of the chemical composition of agricultural vegetation samples collected in the area of copper-pyrite ore deposit location. During the analysis, all samples were divided into three clusters. One can suggest that this separation may be due to different mechanisms of pollutants entry into the particular sampling sites, as well as to the location of these sampling sites relatively to the enterprise industrial area. According to the results of the study, it can be concluded that cluster analysis is an effective tool for distinguishing the zones being characterized by different pollution mechanisms of grassy vegetation, when there are a small number of measurements and relatively low levels of the samples pollution.

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Statistical analysis and forecasting of extraction and use of natural resources

Cited by 7 publications

References 3 publications

Trend Analysis of Total Affected Water and Total Discharged Wastewater of Nišava District (Serbia)

Trend Analysis of Total Affected Water and Total Discharged Wastewater of Nišava District (Serbia)

Prediction of Delivered Quantities of Drinking Water and Discharged Wastewater of the Nišava District (Serbia)

On the application of cluster analysis for vegetation pollution assessment in the area of mining enterprise

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