Кафедри
Постійне посилання на розділhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/35393
Переглянути
6 результатів
Результати пошуку
Документ Examining the ethical considerations of using artificial intelligence in business management(Видавничий дім "Гельветика", 2024) Ivchyk, Vasyl; Shmatko, NataliiaThis article is about ethical considerations surrounding the integration of artificial intelligence (AI) in business management. As AI technologies become increasingly ubiquitous in decision-making processes and operational functions, businesses face a myriad of ethical challenges. From concerns about algorithmic bias and transparency to implications for the workforce and data privacy, the ethical implications of AI in business management are profound and multifaceted. This comprehensive analysis explores real-world examples, ethical frameworks, and best practices to help businesses navigate these challenges responsibly. By addressing these ethical dilemmas head-on, businesses can leverage the benefits of AI while upholding ethical principles and societal values.Документ Electricity demand management as a supplement to distributed generation(2023) Pantielieieva, Iryna; Glushko, Alyona; Shmatko, NataliiaToday, the energy industry is undergoing a radical transformation, the main engine of which is technological innovations, which provide opportunities for the transition to a fundamentally new stage of development. In recent years, there have been changes that forced a rethinking of the requirements for generation facilities, network infrastructure and, in general, the organization of the electricity industry and electricity markets. The increasing wear and tear of equipment, the involvement of distributed energy resources, the change in the role of traditional sources of energy and heat carriers, the growth of demand for electricity and the transformation of its quality characteristics, the change in the behavior of consumers - all this requires the study of the factors of the spread of new technologies in electricity for the transition to the next energy system. Therefore, the modern concept of the development of the electric power industry envisages increasing the active role of electricity consumers. The consumer moves away from the position of «passive» consumption and gets the opportunity to actively change his load with the help of his own (distributed) generation or demand management measures. The article analyzes the possibility of accounting for distributed generation and demand management when planning the development of electric power systems. The method of their joint examination with the help of a «virtual power plant» is described.Документ Identification of Parameters of Electrical Signals in Order to Control Energy Facilities(2021) Pantielieieva, Iryna; Shmatko, Nataliia; Oliinyk, Yuliia; Glushko, AlyonaMethods of statistical estimation of signal parameters are generalized. The errors of correlation estimates, which are caused by the non-integer number of half-periods of the analyzed signal, are analyzed. The application of correlation functions to solve the problem of increasing the accuracy of estimates of the phase shift and the amplitude of the electrical signal over a limited time interval is presented. The information on development of correlation functions for the decision of problems of fast estimation of the increased accuracy of a phase shift and amplitude of an electric signal changing sinusoidally, industrial frequency on a time interval making a part of its period is presented. The practical check of accuracy and fast action of algorithms is given.Документ Unleashing the capabilities of artificial intelligence in managing businesses(Teadmus OÜ, 2024) Shmatko, Nataliia; Ivchyk, VasylThe article delves deeply into the profound impact of artificial intelligence (AI) on contemporary business management, elucidating its multifaceted applications, intricate challenges, and abundant opportunities. Crafted by seasoned experts in the field, the article introduces a novel approach to AI integration, advocating for a synergistic balance between routine and innovative applications to foster strategic adaptability. Drawing upon an exhaustive examination of existing literature and empirical research findings, the authors meticulously detail AI's transformative potential across various domains of business management, encompassing decision-making, operational efficiency, customer experiences, innovation, risk management, and market forecasting across diverse industries. The authors illuminate how organizations can utilize AI's latent capabilities to anticipate market shifts, optimize processes, personalize interactions, and achieve sustainable competitive advantage through pilot projects, continuous learning mechanisms, ethical AI practices, and robust measurement frameworks. Ultimately, this article positions AI integration as an evolutionary journey, reshaping organizational strategies, operational paradigms, and customer engagement frameworks to drive innovation-led growth and secure market leadership in the ever-evolving business landscape. AI tools can assist employees by automating repetitive tasks, providing personalized recommendations, and facilitating collaboration, leading to increased productivity and job satisfaction. Moreover, AI should streamline processes, automate tasks, and optimize resource allocation, leading to increased efficiency and reduced operational costs. Overall, the strategic integration of AI into company operations can drive performance improvements, enhance competitiveness, and position the organization for future success. However, it's essential for companies to address challenges such as data privacy, ethical considerations, and organizational change management to fully realize the benefits of AI implementation.Документ Implementation of artificial intelligence: prospects and challenges for business management(Національний транспортний університет, 2023) Shmatko, Nataliia; Ivchyk, VasylДокумент Unlocking the potential of artificial intelligence in business management(Teadmus OÜ, 2023) Shmatko, Nataliia; Ivchyk, Vasyl