Алескеров Фуад Тагиевич

Network analysis of economic sectors in the world economy

2024 · ARTICLE · en

We consider a network of intermediate inputs trade between sectors of OECD Countries’ in 2020. Centrality indices are used to identify most vulnerable sectors in the network of intermediate inputs trade between 45 manufacturing and non-manufacturing sectors of 76 countries. The network is based on the official data of inter-country input-output tables published in 2023 by OECD. We apply new centrality indices to identify sectors, which might be under the risk in case of an economic shock.

Networks under deep uncertainty concerning food security

2024 · ARTICLE · en

We propose new models to find the vulnerable countries in terms of food security. These models are based on network analysis under deep uncertainty. The conditions of deep uncertainty affect the supply and demand of food, namely, carbohydrates of the countries. Under such conditions networks of the carbohydrate supply between countries are constructed. The countries vulnerability in terms of food security were studied by new centrality indices taking into account carbohydrate consumptions of countries and the possibility of group influence of countries to a country. Also, our models show direct and indirect dependence on import of carbohydrates from other countries. The scenario of one of such situations was constructed, and our models for studying this situation were tested. The vulnerable countries are identified in terms of carbohydrate consumption from main crops in different scenarios based on real data using our new models. The developed models can make the food policy of countries more efficient.

Short-Term Covid-19 Incidence Prediction in Countries Using Clustering and Regression Analysis

2023 · CHAPTER · en

As of February 07, 2022, more than 395 million cases of COVID-19 had been identified in the world, with 5.74 million deaths. The paper considers methodology for predicting the number of cases in the short term using a preliminary assessment of countries based on three indicators: expert assessments of the law-abiding population, the level of education and restrictive measures taken in the country. The description and composition of the groups obtained are given. An assessment of the accuracy of the forecast results is made. A comparison of the considered models of 2020 with 2022 is given.

Network analysis of publications on studies of Parkinson Disease

2023 · ARTICLE · en

More than 10 million people worldwide are suffering from Parkinson Disease (PD). We analyse publications on studies of PD over the period from 2015 to 2021. We have collected about 70 thousand papers from 4912 different journals. After the data preprocessing 39811 publications and 3292 journals are left. Methods of centrality analysis have been applied to identify the most significant publications and journals in the field. Classical and new centrality indices have been evaluated for the whole period and for each year. It can be noticed that changing the parameters makes it possible to extract groups of specialized journals and fields of study, which intensively cite each other.

On the Individual and Coalitional Manipulability of q-Paretian Social Choice Rules

2023 · CHAPTER · en

We study the degree of individual and coalitional manipulability of q-Paretian social choice rules under Impartial Culture. Manipulability is defined as a situation, when an agent or a coalition, which consists of some agents, misrepresents her/their preferences to obtain a better outcome of the social choice rule. We study a class of q-Paretian social choice rules, which consists of four rules: Strong q-Paretian simple majority rule, Strong q-Paretian plurality rule, Strongest q-Paretian simple majority rule, and Condorcet practical rule. For the cases of 3, 4, and 5 alternatives and for the cases from 3 to 100 agents, we use computer modelling to calculate a number of manipulability indices. We provide the analysis of the results for different cases.

The network analysis of oil trade under deep uncertainty

2023 · ARTICLE · en

Oil is essential in many spheres of industries and play key role in economies of different countries. A reduction in oil supplies or production may affect thesituation in a country. We have constructed a network of export/import of oil and analyzed scenarios when a reduction in the oil supply takes place. The countriesmost dependent on imports of oil have been identified.

V Российский экономический конгресс «РЭК-2023». Том XV. Тематическая конференция «Банки, деньги и финансовые рынки» (сборник тезисов докладов)

2023 · BOOK · ru

Superposition Principle for Tornado Prediction

2023 · CHAPTER · en

New Centrality Measures in Networks: How to Take into Account the Parameters of the Nodes and Group Influence of Nodes to Nodes

2022 · BOOK · en

Over the last number of years there has been a growing interest in the analysis of complex networks which describe a wide range of real-world systems in nature and society. Identification of the central elements in such networks is one of the key research areas. Solutions to this problem are important for making strategic decisions and studying the behavior of dynamic processes, e.g. epidemic spread. The importance of nodes has been studied using various centrality measures. Generally, it should be considered that most real systems are not homogeneous: nodes may have individual attributes and influence each other in groups while connections between nodes may describe different types of relations. Thus, critical nodes detection is not a straightforward process. New Centrality Measures in Networks presents a class of new centrality measures which take into account individual attributes of nodes, the possibility of group influence and long-range interactions and discusses all their new features. The book provides a wide range of applications of network analysis in several fields – financial networks, international migration, global trade, global food network, arms transfers, networks of terrorist groups, and networks of international journals in economics. Real-world studies of networks indicate that the proposed centrality measures can identify important nodes in different applications. Starting from the basic ideas, the development of the indices and their advantages compared to existing centrality measures are presented. Features: Built around real-world case studies in a variety of different areas (finance, migration, trade, etc.) Suitable for students and professional researchers with an interest in complex network analysis Paired with a software package for readers who wish to apply the proposed models of centrality (in Python) available at https://github.com/SergSHV/slric

Networks under Deep Uncertainty

2022 · ARTICLE · en

We construct a model to find the insecure countries in terms of food security using network analysis under the conditions of deep uncertainty. The conditions under deep uncertainty can be drought, flood, earthquakes, etc., which affect the supply and demand of food of the countries. Under such conditions which countries are more vulnerable has been studied. In order to study such situations, a model for healthy consumption of different products has been built, and a network is constructed to determine the vulnerable countries using the import and export data of basic food products (Rice, Wheat, Maize, Sorghum, Barley and Rye) for various countries. Different measures of network analysis have been applied and studied to discover the dependency of one country from other country or countries for food supply. The result of the study will definitely be helpful to the countries to resist such threats beforehand.