Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...
The "K-shaped" economy has been top of mind for consumers, corporate leaders, policymakers and investors since the Covid pandemic drastically reshaped Americans' financial habits almost six years ago.
When the weather gets cold in Florida, gators stop eating and iguanas start dropping. How do low temps affect the invasive ...
Abstract: This paper presents a new method that combines deep k-means clustering with granule mining approaches to utilise contextual information for improving outlier detection and classification.
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