Персона: Будзко, Владимир Игоревич
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Training Multilingual and Adversarial Attack-Robust Models for Hate Detection on Social Media
System Analysis of Subject Identification of Digital Twin in Agriculture
Mathematical modeling of evaluating the effectiveness of using RSD data in precision farming
© 2020 Elsevier B.V.. All rights reserved.The tendencies of digital transformation of agriculture towards precision production of agricultural products using Earth remote sensing data, which have become one of the main drivers of the rapid development of the industry around the world, are considered. It is shown that these technologies are currently evolving from the digitalization of individual operations to the digitalization of an interconnected complex with the integration of all operations, including operations of related industries. An analysis of the problems of achieving effective implementation of digital technologies in Russia is given, as well as ways of solving them on the basis of complex, integration technologies. The transformation of agriculture into industrial production due to its digital transformation requires the development of methods for evaluating the economic efficiency of investing a new asset - precision farming technology and remote sensing of the Earth. The article presents the author's mathematical model for evaluating the economic efficiency of using these technologies. Possible options for using this model for the purpose of a scientifically grounded approach to the development of these technologies in the country are discussed.
Fundamentals of an Intelligent System for Computer-Aided Design of Crop Rotations
Deep learning approaches to mid-term forecasting of social-economic and demographic effects of a pandemic
© 2020 Elsevier B.V.. All rights reserved.The COVID-19 outburst has brought serious demographical, economic, and social impacts. Moreover, in large countries, these consequences can vary from region to region. Therefore, authorities and experts lack the models to predict these various impacts at the regional level. This paper presents deep neural network models to do a mid-term forecast of the COVID-19 effect in the Russian regions. The models are based on the various recurrent and sliding-window architectures and utilize the attention mechanism to consider the indicators of the neighbor regions. These models are trained on various data, including daily cases and deaths, the diseased age structure, transport availability of the regions, and the unemployment rate. The experimental evaluation of the models shows that the demographic and healthcare indicators can significantly improve mid-term economic impact prediction accuracy. We also revealed that the neighboring regions' data helps predict the pandemic's healthcare and demographical impact. Namely, we have detected improvement for both the number of infected and the death rate.
Architecture solutions for the metadata extraction toolkit, taking into account the built-in privacy extracts
System Analysis of Educational Digital Ecosystems in the Agro-Industrial Complex of Russia
Mathematical models of control in Digital Economy platforms
© 2020 Elsevier B.V.. All rights reserved.The article examines the problems of the functioning of economic systems in which production, distribution, exchange and consumption are carried out on the basis of digital technologies. These circumstances stimulate the creation of new economic models of interaction and management, corresponding to new information opportunities at different levels of the organizational structure of economic systems. Along with the arrays of deterministic data at the disposal of independent economic agents and management structures, there are representative volumes of data on the implementation of uncontrollable factors. Particular interest in the work is shown in agricultural technologies, which, along with the volatility of demand for products, are characterized by indefinite natural fluctuations, which requires the development of special models and specific mechanisms for coordinating activities. A series of different economic models is presented, reflecting the possibilities of creating coalitions of active agents. The issues of centralization and decentralization in the management of economic systems are also fundamental. For the analysis and synthesis of control systems, a spectrum of models of the functioning of economic agents is presented, for which various forms of information and various classes of behavior strategies are available.