In the paper the problem of formalization and identification of real and virtual information objects and traceability of their relations in the studied subject domain using the rules of monomorphism and polymorphism of the mathematical theory of sets and categories is investigated. According to the principles of the systems engineering standard ISO/IEC 15288 models and methods of analytical software creation are developed. It is shown that the structure of such analytical software meets the conditions of Cartesian closed logic that considerably expands the range of tasks, which can be solved using this software. This is made possible because the effective reengineering of the software can be carried out in real time mode without any changes of its program code. The formalized description of the relations between virtual and real objects using the rules of data storages is offered. The method of creation of Chomsky hierarchies and a method of Osgood's semantic differentials are applied. As an example the structure of the distributed analytical software of the talent pool management of the industrial enterprise formed together with educational institutions of the higher education is considered.
Data processing facilities anD systems Куликов Г.Г. Kulikov G.G. д-р техн. наук, профессор кафедры «Автоматизированные системы управления», ФГБОУ ВО «Уфимский государственный авиационный технический университет», г. Уфа, Российская Федерация Антонов В.В. Antonov V.V. д-р техн. наук, заведующий кафедрой «Автоматизированные системы управления», ФГБОУ ВО «Уфимский государственный авиационный технический университет», г. Уфа, Российская Федерация Фахруллина А.Р. Fakhrullina A.R. канд. техн. наук, доцент кафедры «Автоматизированные системы управления», ФГБОУ ВО «Уфимский государственный авиационный технический университет», г. Уфа, Российская Федерация
The concept of "Digital Transformation 2030", which defines the national goals and strategic objectives of the development of the Russian Federation for the period up to 2030, specifies specialized goals and objectives that are an important message for the introduction of intelligent information management technologies in the electric power industry. The main challenges for the transition to digital transformation are the increase in the rate of growth of tariffs for the end consumer, the increasing wear and tear of the network infrastructure, the presence of excessive network construction and the increase in requirements for the quality of energy consumption. The determining factor in the possibility of developing an effective energy policy is the forecasting of electricity consumption using artificial intelligence methods. One of the methods for implementing the above is the development of an artificial neural network (ANN) to obtain an early forecast of the amount of required (consumed) electricity. The obtained predictive values open up the possibility not only to build a competent energy policy by increasing the energy efficiency of an energy company, but also to carry out specialized energy-saving measures in order to optimize the organization’s budget. The solution to this problem is presented in the form of an artificial neural network (ANN) of the second generation. The main advantages of this ANN are its versatility, fast and accurate learning, as well as the absence of the need for a large amount of initial da-ta for a qualitative forecast. The ANN itself is based on the classical neuron and the error back-propagation method with their further modification. The coefficients of learning rate and sensitivity have been added to the error backpropagation method, and the coefficient of response to anomalies in the time series has been introduced into the neuron. This made it possible to significantly improve the learning rate of the artificial neural network and improve the accuracy of predictive results. The results presented by this study can be taken as a guideline for energy companies when making decisions within the framework of energy policy, including when carrying out energy saving measures, which will be especially useful in the current economic realities.
Введение Свой ства двойственности (противоположности, противоречивости) отношений-транзакций между виртуальными объектами в информационной среде-определяются как спецификой объектов, так и свойствами самой среды. Так, например, согласно статистическим данным за 2018 год, правоохранительными органами Российской Федерации было зарегистрировано более 100 тыс. преступлений, совершенных с использованием информационно-телекоммуникационных технологий. По сравнению с 2017 годом количество такого рода преступлений возросло более чем на 33 %. За последние 6 лет киберпреступность, согласно статистике, демонстрирует десятикратный Информатика и вычислительная техника УДК 004.4
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