Кафедра штучного інтелекту та математичного моделювання
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Item type:Наукова стаття, Digital Technologies in the Process of Teaching STEM Disciplines: Challenges and Prospects(2024-03-28) Hubal, Halyna; Siasiev, Andrii; Sipii, Volodymyr; Syrmamiikh, Iryna; Burtovyi, SerhiiThe modern integration of digital technologies into the educational process requires additional study, given the opportunities that this process opens up. The purpose of the article is to study the use of digital technologies in STEM educ ation through the prism of researching the main challenges and prospects. To achieve this goal, the methods of questionnaires and interviews were used. In particular, 65 teachers of higher education institutions were interviewed, whose opinions became the basis for forming a generalised picture of the study. The results show that modern teachers actively use digital technologies in STEM education. The average level of digital technology use among STEM teachers is high: 43 people (65%) use technology at grade levels 4 and 5. However, this intensive use of digital technologies in STEM education raises both challenges and opportunities. In particular, today's teachers often face limited access to the necessary technical infrastructure, which can limit their ability to implement digital tools. Poor quality of internet connection can affect the smoothness and efficiency of using online resources. Insufficient training of teachers in the use of digital technologies is also a significant challenge. Incre asing the availability of digital resources for teachers will make learning more accessible and diverse. Cooperation between universities and technology companies also opens up new opportunities for the development of STEM education. The conclusions emphasise that such interaction facilitates the exchange of experience, access to advanced technologies and resources, and creates conditions for the implementation of joint projects and programmes.Item type:Наукова стаття, Evaluation of the effectiveness of decision-making algorithms in the management of renewable energy sources: A case study of Ukraine(2025) Siasiev, Andrii; Dudnikov, Serhii; Nikolaienko, Dmytro; Hubal, Halyna; Bondarchuk, OlegThe integration of renewable energy sources in Ukraine requires advanced decision-making algorithms to address various challenges, including energy forecasting, resource optimization, and grid stability. The existing algorithms exhibit limitations in accuracy and efficiency, necessitating the development of innovative approaches to enhance performance in this regard. This work evaluated the performance of existing algorithms and developed two new algorithms: the enhanced forecasting algorithm (EFA) and the dynamic resource optimization algorithm (DROA). Data from a hybrid energy system comprising solar, wind, and battery storage was used for analysis. The algorithms were assessed based on forecasting accuracy, economic efficiency, and system stability. Moreover, key metrics like mean absolute percentage error (MAPE) and operational cost reductions were used for the evaluation in the current work. According to the analysis results, the EFA achieved a 54% improvement in forecasting accuracy and reduced MAPE to 5.8%. The DROA enhanced resource optimization, resulting in a 56% reduction in energy losses and an 18% decrease in operational costs. System stability was improved, and grid frequency fluctuations were reduced by 67%. These results demonstrated the superiority of these new algorithms over existing methods. This work highlighted advanced algorithms' critical role in optimizing Ukraine's renewable energy systems. The EFA and DROA demonstrated significant potential for operational and economic benefits. This is possible with improved energy forecasting, reduced losses, and enhanced grid stability. Future research endeavors should focus more on applications and explore additional performance metrics to optimize energy systems in this regard.