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, ...
Mr. Means quietly departed his federal role about a month ago. His sister has been nominated for surgeon general. By Benjamin Mueller Calley Means, an influential adviser to Health Secretary Robert F.
ABSTRACT: Stock returns exhibit nonlinear dynamics and volatility clustering. It is well known that we cannot forecast the movements of stock prices under the condition that market is efficient. In ...
Rocky high steep slopes are among the most dangerous disaster-causing geological bodies in large-scale engineering projects, like water conservancy and hydropower projects, railway tunnels, and metal ...
Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...
Abstract: This paper proposes an improved K-means clustering algorithm based on density-weighted Canopy to address the efficiency bottlenecks and clustering accuracy issues commonly encountered by ...
Clustering can take a long time when there is a large number of submissions. Users who are not interested in clustering can safely disable it with the --cluster-skip option. Clustering can either be ...
ABSTRACT: Accurate sales forecasting is essential in the fast-paced world of business for effective strategic planning and resource allocation. However, traditional forecasting methods often lack ...
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