joint spectral clustering and feature-based pricing and show that our policy achieves near-optimal performance, i.e., its … clustering and feature-based pricing with different types of feature heterogeneity. Our case study based on real-life smart meter …

the hierarchical clustering evolves over time by varying the threshold of inconsistency, the variation of information … shows that during a period of a financial crisis, the structure of hierarchical clustering has a small tendency to change … dynamic hierarchical using the Fisher distance gives less-variant clustering and can shed more insights into stock behaviors …

patterns are rarely found. In this study, a hierarchical clustering algorithm coupled with principal component analysis is used … 90% of the variance. After the data pre-processing process, the hierarchical clustering algorithm is implemented with the … coefficients, and clustering structures. The results of the hierarchical clustering depict that each cluster detects a unique range …

clustering method for short-term load forecasting. User clusters with similar electricity consumption habits could be separated …

-medoid clustering. To ensure a broader variation of the cloud movements, neighbouring stations are also used, selected using Dynamic …, the current weather condition is matched with the different weather groups found through clustering, and subsequently, a …