Situational-scenario approach to formation costs of production and technological activities of fishing vessels on voyage

Increasing the efficiency of tapping the aquatic biological resources by fishing vessels directly depends on the improvement of production and technological activities in the unpredictable field conditions. Like any production process, the production and technological activity of fishing vessels is associated with the occurrence of costs at all stages (phases) of the production process, the aggregate and structure of which depends on the fishing technological system of the fishing vessel. The stages of the production process form the main material flow, ensuring its end-to-end promotion. Its efficiency significantly affects the costs and management of field resources and should be achieved by minimizing material losses, primarily in the process of extracting raw materials. For this, it is necessary to study the field conditions in which the production and technological process takes place within the framework of the production vessel, determine their structure, variability, analyze the structure and composition of production costs at all phases of the production and technological process, develop a situational and scenario approach to the formation of production and technological activities of fishing vessels on a fishing trip. The costs arising in all subsystems (phases) and operating on a constant basis throughout the entire fishing period are proposed to be divided into several types of costs. Their interrelated and interdependent influence can give both a general determinism to the production process and increase its imbalance, increasing the total fishing costs of a producing vessel due to the emergence of additional costs associated with an unstable fishing situation in the fishing area. In this regard, the production activity on the fishing vessel is carried out according to the formed fishing and technological scenarios. The developed block diagram of the totality of fishing costs during the movement of the main material flow through the phases of the fishing and technological system of a fishing vessel gives a complete picture of the total fishing costs of a fishing vessel when it simultaneously performs the processes of extraction and processing of aquatic biological resources with a situational-scenario approach to their formation.

Prediction of COVID-19 pandemic dynamics in Russia based on simple mathematical models of epidemics

Introduction: The COVID-19 pandemic which began in 2020 and has taken more than five million lives has become a threat to the very existence of mankind. Therefore, predicting the spread of COVID-19 in each individual country is a very urgent task. The complexity of its solution is due to the requirement for fast processing of large amounts of data and the fact that the data are mostly inaccurate and do not have the statistical properties necessary for the successful application of statistical methods. Therefore, it seems important to develop simple forecasting methods based on classical simple models of epidemiology which are only weakly sensitive to data inaccuracies. It is also important to demonstrate the feasibility of the approach in relation to the incidence data in Russia. Purpose: Obtaining forecast data based on classical simple models of epidemics, namely SIR and SEIR. Methods: For discrete versions of SIR and SEIR models, it is proposed to estimate the parameters of the models using a reduced version of the least squares method, and apply a scenario approach to the forecasting. The simplicity and a small number of parameters are the advantages of SIR and SEIR models, which is very important in the context of a lack of numerical input data and structural incompleteness of the models. Results: A forecast of the spread of COVID-19 in Russia has been built based on published data on the incidence from March 10 to April 20, 2020, and then, selectively, according to October 2020 data and October 2021 data. The results of the comparison between SIR and SEIR forecasts are presented. The same method was used to construct and present forecasts based on morbidity data in the fall of 2020 and in the fall of 2021 for Russia and for St. Petersburg. To set the parameters of the models which are difficult to determine from the official data, a scenario approach is used: the dynamics of the epidemic is analyzed for several possible values of the parameters. Practical relevance: The results obtained show that the proposed method predicts well the time of the onset of the peak incidence, despite the inaccuracy of the initial data.

Scenario approach to agricultural development in Azerbaijan

The purpose of this paper is to substantiate the optimal scenario to develop agriculture for the effective diversification of the Azerbaijani economy. By constructing an intersectoral balance model and using regression analysis, we propose the approach for determining optimal agriculture development scenarios taking into account the current development trends of the industry: innovative, inertial, and balanced. Using the balance model helps to account for the cause-and-effect relationships between the indicators of the development of all sectors of the Azerbaijani economy and comprehensively assess the impact of agricultural development on the diversification of the national economy. In contrast to the classical balance model, the modified model proposed in our article provides possibilities to assess not just the production potential of industries but also their contribution to the formation of the country's GDP and diversification of the economy on the way to neutralizing oil dependence.

Socio-economic development scenarios of the White Sea regions.

In the process of creating a national system of strategic planning and within the framework of normative economics, the scenario approach provides opportunities for constructing goals and directions of socio-economic territories development. Being a planning tool the scenario approach allows forming the directions of regional development. These processes take particular relevance for the regions of our country that are the parts of the Arctic zone, especially in increased interest and attention to these territories resources from other external agents. The main aim of this paper is to elaborate development scenarios for the regions, which are fully or partially included in the Arctic zone and the White Sea catchment area. Based on the dynamics analysis of the main macroeconomic indicators and development trends for 1990–2019, the dependence of indicators for forecasting socio-environmental and economic development of these regions, was built. We applied scenario approach to describe possible development scenarios of Arctic regions in the White Sea catchment area. The novelty of the work is the construction of matrix of development scenarios of the Arctic regions, united by belonging to the White Sea catchment area. The analysis results of macroeconomic indicators for three elements of sustainable development show that the regions have rather weak economic development, stagnation of social indicators and difficult environmental situation. We outlined the problems constraining the development of Arctic regions in the White Sea catchment area and the directions to their solutions. To reach the trajectory of sustainable development is possible under condition of coordination and implementation of the measures taken by the state and regional authorities. This scenario of development strategy according to the innovation trajectory will allow to consolidate activity of federal, regional and municipal authorities of these territories. The integrated development program of the Arctic regions in the White Sea catchment area can be a coordinating platform.

Scenario approach to assessing the prospects for the impact of the COVID-19 pandemic on the economy of countries (using the example of the United States, China and Russia)

The article is devoted to the study of the phenomenon of the scenario approach to assess the prospects for the impact of the COVID-19 pandemic on the economies of countries using the example of the largest world leaders: the United States, China, Russia. The emerging global epidemiological problem is a serious constraining factor for the development of the economies of states. From the point of view of scientifi c novelty, the analysis and assessment of development scenarios for the economies of the studied states can become the basis for drawing up an action plan to eliminate the consequences of the COVID-19 pandemic. To this end, within the framework of this work, scenarios of further development were considered for each of the countries. For Russia, the following scenarios were chosen baseline scenario — the pace of development of the world economy will be slow, full recovery will take place at the end of 2023; deflationary scenario — in this scenario, the impact of the COVID-19 pandemic, as well as the current restrictions, will persist for a long time. At the same time, oil prices will reach $ 50 per barrel only after 2023, inflation by 2023 will reach 1.5-2.5 %; pro-inflationary scenario — the effects of the pandemic will subside quickly enough, but the potential level of output in the global economy will fall deeper. At the same time, oil prices by 2023 will be $ 42–43 per barrel; risk scenario — within the framework of this scenario, the possibility of a repeat of the COVID-19 pandemic is allowed and the tightening of restrictive measures, which will negatively affect the economies of states, is not excluded. The choice of the studied states was determined not only by world leadership, but also by the degree of influence of the coronavirus on their economies. During the study, a forecast of key indicators of the economies of the United States, China and Russia for 2021 was carried out, the prospects for their dynamics in the current economic situation were assessed, and the main trends followed by the governments of states were examined and identified.

Resilient Predictive Control Coupled with a Worst-Case Scenario Approach for a Distributed-Generation-Rich Power Distribution Grid

In a context of accelerating deployment of distributed generation in power distribution grid, this work proposes an answer to an important and urgent need for better management tools in order to ‘intelligently’ operate these grids and maintain quality of service. To this aim, a model-based predictive control (MPC) strategy is proposed, allowing efficient re-routing of power flows using flexible assets, while respecting operational constraints as well as the voltage constraints prescribed by ENEDIS, the French distribution grid operator. The flexible assets used in the case study—a low-voltage power distribution grid in southern France—are a biogas plant and a water tower. Non-parametric machine-learning-based models, i.e., Gaussian process regression (GPR) models, are developed for intraday forecasting of global horizontal irradiance (GHI), grid load, and water demand, to better anticipate emerging constraints. The forecasts’ quality decreases as the forecast horizon grows longer, but quickly stabilizes around a constant error value. Then, the impact of forecasting errors on the performance of the control strategy is evaluated, revealing a resilient behaviour where little degradation is observed in terms of performance and computation cost. To enhance the strategy’s resilience and minimise voltage overflow, a worst-case scenario approach is proposed for the next time step and its contribution is examined. This is the main contribution of the paper. The purpose of the min–max problem added upstream of the main optimisation problem is to both anticipate and minimise the voltage overshooting resulting from forecasting errors. In this min–max problem, the feasible space defined by the confidence intervals of the forecasts is searched, in order to determine the worst-case scenario in terms of constraint violation, over the next time step. Then, such information is incorporated into the decision-making process of the main optimisation problem. Results show that these incidents are indeed reduced thanks to the min–max problem, both in terms of frequency of their occurrence and the total surface area of overshooting.