and infrastructure along the value chain. Spatial clustering to identify the subregions can lead to a better … indicators and their evaluation regarding different objectives are seen to be transferable to other clustering and …

clustering of empirical survey data, aims to identify clusters of behavioral intentions for using VR in tourism based on an …

Development Index (HDI) through Multiple Factor Analysis (MFA) and hierarchical clustering to create a comprehensive perspective … on global development. By clustering countries based on these indicators, the analysis reveals distinct profiles …, offering sustainable development models. MFA and hierarchical clustering have proven effective in categorising countries with …

intelligence adoption process, its dynamics and patterns using principal component analysis and K-means clustering. The results …

. To address this question, we propose a weighted compositional clustering approach aimed at tackling the trajectories and …

introduce a comprehensive framework that incorporates temporal clustering of development factors and addresses associated …

proposes a method based on Graph Clustering Neural Networks to analyze and study urban functional areas. To begin with, the …-economic characteristics. Through the use of Graph Clustering Neural Networks and clustering algorithms, urban functional areas can be … identified through clustering through the integration of Graph Neural Networks and clustering algorithms. For functional area …