Scenarios for the development of the Arctic region (2020–2035)

Зайков, Константин; Kondratov, Nikolay; Kudryashova, Elena; Lipina, Svetlana; Chistobaev, Anatoliy I.

doi:10.17238/issn2221-2698.2019.35.5

Cited by 27 publications

(5 citation statements)

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“…Given that the adequacy of the results obtained at this stage is a determining factor affecting the quality of the models formed, it is obvious that additional verification of the conclusions made by methods that use completely different principles and methodology is necessary. To solve the problem of verification of the obtained results, the algorithm of intellectual analysis (Zaikov et al, 2019;Tikhonov, 1985; Williams, 2011) -decision trees -was used. When processing the data by the decision tree algorithm (using the implementation from sci-kit learn, with the following parameters: the evaluation criterion -MSE; the tree depth -5; the minimum number of samples in one sheet -5), the values of the importance of the initially considered features were obtained (see Table 3), on the basis of which the conclusion about five the most intensively influencing the target function parameters (taking into account the pair correlation with other factors) was fully confirmed, which made it possible to proceed to the next stage of the study -the creation of regression models themselves.…”

Section: Resultsmentioning

confidence: 99%

Formation of a complex method for analyzing multidimensional production data of a processing plant

Ivashchuk¹,

Ivashchuk²,

Fedorov³

et al. 2021

EA-XXI

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We discuss the development of a comprehensive data analysis method which allows increasing the accuracy of predicting the performance of roller mill of processing plant (RP) mining and processing plant (GOK) when you change the properties of incoming raw materials for processing. The described method includes primary data processing, determination by statistical analysis methods and data mining algorithms of the most significant factors affecting the resulting parameter, development of mathematical models based on correlation regression and factor analysis, analysis and confirmation of the quality of forecasting by a neural network. The systematization and coordination of production data was carried out, the generated database was processed using statistical and intellectual analysis methods, the physical and chemical parameters of the input raw materials and processed ore that have the greatest impact on the mill productivity were determined, mathematical models were formed to determine the expected productivity, their quality and applicability limits were evaluated, the error in predicting the mill productivity for various mineralogical compositions of the processed ore was determined. The significance of the parameters used in the models is checked by the algorithms of intelligent analysis. The verification of the used models for predicting mill performance by an artificial neural network is carried out by comparing the series of predicted values of the resulting factor obtained by different models

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Section: Resultsmentioning

confidence: 99%

Formation of a complex method for analyzing multidimensional production data of a processing plant

Ivashchuk¹,

Ivashchuk²,

Fedorov³

et al. 2021

EA-XXI

View full text Add to dashboard Cite

show abstract

“…[7], Zaikov K.S., Kondratov N.A., Kudryashova E.V., Lipina S.A. and Chistobaev A.I. [8], Karginova-Gubinova V.V., Vasilieva A.V., Moroshkina M.V., and Potasheva O.V. [9], and others, including the authors [10].…”

Section: Introductionmentioning

confidence: 99%

Agriculture in the Polar Regions: New Approaches to Historical Challenges

Yakovenko,

Arkhipov

2024

BIO Web Conf.

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The implementation of the Northern Sea Route Development Programme aims to increase the permanent population of the Arctic zone of Russia. This problem cannot be solved without a corresponding enhancement of the food supply of the Arctic. The importance of the study is conditioned by the need to modernize the system of food supply of the Arctic territories in the context of external threats. The article examines approaches to developing agriculture and solving the problem of food security in the Arctic regions of Russia. The authors consider the possibilities of the permanent population of the Arctic to produce enough food for their own consumption and the influence of preferential regimes on the development of agriculture and the solution of food security. The authors have analyzed the current regulatory acts and the results of their implementation in the Arctic zone of the Russian Federation, based on which an assessment of the state policy’s performance in modern conditions is given, together with the authors’ recommendations for addressing the abovementioned task.

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“…The Russian Arctic zone is among the key directions in the development of the Russian national economy, contributing to the development of mining and transportation of minerals, accessibility and autonomy of remote settlements, international cooperation, and the national image. Russian Federation has the largest Arctic sector among the countries that have an outlet to the Arctic Ocean, a result of which is that it has a leading role as a developer of the Arctic development strategy [1]. It is assumed that the Northern Sea Route (NSR), which is a major transport corridor in the Arctic area, will operate uninterrupted and year-round by 2030 according to the Arctic development plan [2].…”

Section: Introductionmentioning

confidence: 99%

The Construction of Seaports in the Arctic: Prospects and Environmental Consequences

Makarova,

Buyvol,

Mukhametdinov

et al. 2023

JMSE

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The Arctic zone of the Russian Federation is of strategic importance for the country. Considering the fragility of Arctic ecosystems, special attention needs to be paid to the sustainable development of transport and related infrastructure within the framework of the “blue economy” concept, which is relevant for Arctic waters. At the same time, it is necessary to identify the main factors and tasks of creating transport and port infrastructure, building a modern fleet, and organizing fisheries and tourism in an environmentally sound manner. The purpose of the study is to consider the problems of anthropogenic influence for seaport facilities and to create a conceptual model of an environmental risk management system. The existing problems of Arctic ports and infrastructure are analyzed and existing business processes are considered, taking into account the peculiarities of their functioning in Arctic conditions. To systematize environmental assessments and establish dependencies between the main indicators describing the impact of port activities on elements of the natural environment, ontological domain engineering is proposed. It systematizes the basic terminology used within different subject areas of ecology and risks and allows one to visualize the relationships between elements of the natural environment, objects, port systems, their parameters and impact factors to assess the impact of the seaport on the natural environment. The results of ontological engineering (design and development of ontologies) in the field of risk management are presented. Future research will be aimed at developing the applied aspect of applying the results of ontological engineering in terms of specific engineering studies related to the assessment of anthropogenic load on the Arctic territory using simulation modeling.

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Scenarios for the development of the Arctic region (2020–2035)

Cited by 27 publications

References 0 publications

Formation of a complex method for analyzing multidimensional production data of a processing plant

Formation of a complex method for analyzing multidimensional production data of a processing plant

Agriculture in the Polar Regions: New Approaches to Historical Challenges

The Construction of Seaports in the Arctic: Prospects and Environmental Consequences

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