This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.

This research aims to investigate how technological innovation influences social sustainability via the mediating role of organizational innovation and digital entrepreneurship. This investigation employed a quantitative research approach and used data from survey questionnaires based on a set of suppositions evaluated using structural equation modeling. A total of 320 respondent companies from digital provider companies in Thailand. The findings of the research expose that technological innovation has a positive effect on organizational innovation and digital entrepreneurship. Both serve as mediators in the correlation between technology innovation and social sustainability. Moreover, this research will be beneficial for businesses that are implementing new technologies and innovation, considering their role in attaining both environmental and social sustainability.

This study examined the role of cryptocurrencies in tourism and their acceptance across EU regions, with particular attention to the digital transformation precipitated by the COVID-19 pandemic. The analysis focuses on the relationship between cryptocurrency acceptance points and the intensity of tourism, highlighting that the acceptance of cryptocurrencies is significantly correlated with tourism services. The literature review highlighted that Web 3.0, especially blockchain technology and decentralized applications, opens new possibilities in tourism, including secure and transparent transactions, and more personalized travel experiences. The research investigated cryptocurrency acceptance points and the intensity of tourism within the EU. The study illuminates that the acceptance of cryptocurrencies significantly correlates with tourism services. The data and methodology demonstrated the analysis methods for examining the relationship between cryptocurrency acceptance points and tourism intensity, including the use of clustering neural networks and Eurostat data utilization. The results showed a positive correlation between the number of cryptocurrency acceptance points and tourism intensity in the EU, affirming the research hypothesis. According to the regression analysis results, each additional cryptocurrency acceptance point is associated with an increase in tourism intensity. The significance of the research lies in highlighting the growing role of digital payment solutions, especially cryptocurrencies, in tourism, and their potential impacts on the EU economy. The analysis supports that the intertwining of tourism and digital financial technologies opens new opportunities in the sector for both providers and tourists.

The article reveals the problems of the transition to a “green” economy based on sustainable technological changes, which are caused by global ecological pollution of the ecosystem, which leads to warming and ecological changes and the insufficiency of the natural resource potential to meet the needs of the population of the planet, which does not contribute to development. The essence of the study is to determine the impact of a green economy on economic growth and development, in which natural assets continue to provide resources and environmental services. It is shown that the green economy provides a practical and flexible approach to achieving concrete, measurable progress in all its economic and environmental principles, while at the same time fully taking into account the social consequences of greening the dynamics of economic growth. Green economy strategies aim to ensure that natural assets can fully realize their economic potential in a sustainable manner. This potential includes the provision of vital life support services—clean air and water, as well as the sustainable biodiversity needed to support food production and human health. Natural assets cannot be replaced indefinitely, so the policy of the green economy should take this into account. It is characterized that the green economy provides a practical and flexible approach to achieving concrete, measurable progress in all its economic and environmental principles, while at the same time fully taking into account the social consequences of greening the dynamics of economic growth. The problems of the post-war revival of Ukraine’s economy are systematized and proposals for their solution are substantiated, which is the scientific contribution of the authors to the coverage of this problem. The global problems of the transition to a green economy, which are closely related to Ukrainian realities, are revealed. The practical content is determined by the fact that the theoretical and methodological provisions, conclusions and scientific and practical recommendations constitute the scientific basis for the development of a new holistic concept of the development of the green economy of Ukraine. The conclusions that it is the “green” economy that is able to most closely link the ecological and economic aspects of the national economy, acting as a key direction for ensuring the sustainable “green” development of the region and the state as a whole, actualize the prospects of creating a green economy in Ukraine and become necessary and quite achievable in the post-war period.

Based on instructional practice in badminton course teaching, this study expands the application of goal-directed behavior theory from management studies in the field of physical education, thereby supplementing the existing conditions for applying goal-directed behavior theory in the sports domain. Empirical evidence confirms that proactive college students, through the reconstruction of the badminton knowledge system, implementation of innovative teaching methods, and utilization of multidimensional assessment approaches, can effectively acquire proficient skills in major badminton techniques within a 32-hour instructional period. This accomplishment not only achieves the intended teaching objectives but also resolves the issue of students struggling to comprehend and acquire badminton techniques within a limited timeframe.