The article discusses the application possibilities of machine learning methods (artificial neural networks (ANN) and genetic algorithms (GA) to form management actions when applying the concept of situational management for intelligent support of strategic decision-making on the development of energy. At the first stage, the application of ANN to classify extreme situations in the energy sector, to select the most effective management actions (preventive measures) in order to prevent a critical situation from developing into an emergency. Genetic algorithms are proposed to be used to determine the weighting coefficients for training ANN. An algorithm for constructing a classifier based on a neural network and a demonstration task using data on generation and consumption of the United Electric Power System of Siberia are presented.
The article describes proposed by author a fractal approach to knowledge structuring, which actively used for developing to the ontological space of knowledge, primarily in the energy field. We introduce the methodological concept of the fractal information space and the concept of fractal stratified (FS) model. It’s given mathematical description of the FS-model and one method for determining of the fractal dimension. The examples of the application of fractal approach and FS-model in the work carried out under the guidance of author were considered.
The article discusses an approach to the construction of digital twins and digital shadows, based on the use of scientific tools for complex energy research in Russia. It is proposed to use, as their basis, mathematical models of energy systems and software systems and databases developed at the Energy Systems Institute of SB RAS, for calculations using these models. For each area of research, an ontological model is developed, over which mathematical and information models are built and integrated, as the basis of digital twins and digital shadows of energy objects. In turn, scientific prototypes of digital twins and digital shadows can be used in complex energy studies. To support this research, a modified architecture of the multi-agent intelligent environment is proposed. It is considered as the basis of the future IT infrastructure that integrates modern information and intelligent technologies and implements a new approach to building digital twins and digital shadows using scientific tools.
A brief overview of the history of Digital Earth in Russia, its current status and prospects for further development are proposed and discussed in this chapter. The anticipation of the concept of Digital Earth in Russian culture is demonstrated and explained. Conclusions about the specificity of the development of the concept of Digital Earth in Russia due to its geographical, historical and cultural characteristics are drawn, and development factors are revealed. The vital need for the concept in ensuring the effective governance and sustainable development of the country is emphasized. Theoretical and applied results achieved by the Russian Digital Earth community are presented. Special attention is paid to the outreach of the Digital Earth vision to state governance, business, society and education. The key importance of international cooperation for the successful implementation of Digital Earth in Russia is explained.
2. Effective construction of comprehensive software by using the multi-agent approach 2.1 Methodical approach to multi-agent software development Traditionally, there are active complex research of energy systems (electrical power system, natural gas industry, mineral oil providing system, carbon providing system, heat supply system), Fuel Energy Complex (FEC) and energy security problem of Russia in Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences (ESI SB RAS). Results of researching the branch energy systems often are input data for FEC research. And results of researching the developing trends of FEC must be taken into account while analyzing developing process of the branch energy systems. It is necessary to co-ordinate input and output information to get grounded conclusions and recommendations whish are prepared for outer organizations. That is why we must create www.intechopen.com
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