Convergence or Divergence? A Cluster Analysis of Energy Poverty Patterns Across the European Union Amidst Policy Shifts and Crises by Piotr Kosowski

“…Utilizing Eurostat EU-SILC data, the study analyzes trends in four key indicators: the inability to keep homes adequately warm, arrears on utility bills, housing cost overburden rate, and the at-risk-of-poverty rate. Data processing and trend analysis were performed using R and RStudio, while a k-means cluster analysis, executed in Python via Visual Studio Code, identified and compared distinct country groupings based on their energy poverty profiles in 2015 and 2023. …”
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Traffic Pollution Assessment Using Artificial Neural Network and Multivariate Analysis by Mario De Luca, Daiva Žilionienė, Saulius Gadeikis, Gianluca Dell’Acqua

“…Also, the following parameters were detected: wind speed and direction, temperature and traffic flow rate. Data processed with Multivariate Analysis and Artificial Neural Network approach. …”
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