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.

Since the 20th National Congress, with the emphasis on innovation and entrepreneurship on country, innovation and entrepreneurship education has become an important part of talent training in universities. The constructivist learning concept advocates that students' learning should respect their own meaning construction, and social mutual assistance and situational construction to acquire knowledge. Based on the current issue of students' innovation and entrepreneurship, this article takes the constructivist learning perspective as a guide to explore strategies to enhance their innovation and entrepreneurship abilities, and is committed to promoting the improvement of their abilities.

Through the research on the communication mode of rural youth e-commerce, the paper puts forward that there are some advantages and many problems in the e-commerce engaged in.

This paper discusses the construction strategy of innovation and entrepreneurship education path for college students under the background of digital economy. Firstly, this paper analyzes the characteristics of digital economy and its influence on higher education, and then puts forward four core construction paths for college students' innovation and entrepreneurship education: integrating digital skills and knowledge, promoting practice and innovative thinking, interdisciplinary integration and collaborative learning, and linking industry and academia. Each path discusses the specific implementation and expected effect in detail. The purpose of this study is to provide higher education institutions with effective methods and strategies to cultivate students with innovative spirit and entrepreneurial ability in the era of digital economy.

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.

This paper, with its focus on national legislative regulations that have come into force and governments developed policies designed to clear away numerous problems regarding women’s employment has a threefold contribution to the existing literature. First, it summarizes the salient features of the new legislation and administrative measures adopted by the government of Turkyie, with special reference to Bursa Yıldırım Municipality. Second, we draw attention to the increasing recognition of the valuable potential of females in the workplace. Over recent decades and the implications for the central administration but also the private sector, local administration and voluntary agencies. Third, policy syndromes about livelihoods, and hardship alleviation policies, are examined and policy implications are discussed. This paper does not aim to provide definitive answers, yet intends to scrutinize the data and re-examine the trends in the light of key drivers such as economics, demographics, and urbanization. This was done mainly by reviewing the literature government reports and statistical data but was augmented by our fieldwork. There is an attempt to reach a conclusion about recent developments and make suggestions about countermeasures that could be implemented.