Application of ontological analysis tools for the formation of calculation models of power supply

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The concept of intellectual support of the process of automated formation of calculation models of power supply in information systems of energy enterprises, based on the principles of knowledge management, is proposed. The concept includes carrying out ontological data analysis and the formation of the corresponding knowledge bases. The stages of the knowledge management process about the parameters of the calculated power supply models have been decomposed in order to develop tools for their automatic generation in billing systems. Sets of parameters of power supply objects and parameters characterizing the volume of energy consumption, price indicators and parameters for calculating the cost of consumed electricity, which, along with the relations between entities and their functional connections, determine the structure of ontologies, have been determined. For the first time, the definitions of the computational model of power supply are given as a semantic model consisting of a set of basic concepts of the electric power industry, and as a system of knowledge about methods of storing and processing information about the values of energy consumption. An ontology of the process of forming calculation models using the Protégé ontological editor is built. Requirements for the knowledge base of the system for supporting the formation of calculation models in information systems are formulated and the possibility of using data mining technologies with mechanisms for checking the consistency, sufficiency and continuity of knowledge through the use of methods for forming fuzzy rules is substantiated. This makes it possible to substantiate the possibility of applying the principles of fuzzy logic for the automated generation of calculation models of power supply in billing systems.

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Calculation model of power supply, dss, information billing systems, ontological analysis, knowledge bases, fuzzy logic

Короткий адрес: https://sciup.org/170178869

IDR: 170178869   |   DOI: 10.18287/2223-9537-2020-10-4-477-488

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