Robust 'Huber mean' for geometric data protects against noise and outliers

In an era driven by complex data, scientists are increasingly encountering information that doesn't lie neatly on flat, ...
SciELO

Comparison of clustering methods and conventional approaches for geological fracture analysis: A case study in northern Shiraz, Iran

This study investigates the application of advanced clustering methods to geological fracture analysis in the Baba Kohi anticline, located in the folded Zagros region of southwest Iran. The primary ...
Scientific Research Publishing

Application of the K-Means Algorithm in the Study of Influenza Transmission Patterns ()

As a highly contagious respiratory disease, influenza exhibits significant spatiotemporal fluctuations in incidence, posing a persistent threat to public health and placing considerable strain on ...
Scientific Research Publishing

He, M. (2024) Network Anomaly Data Mining and Classification Method Based on Improved K-Means Clustering Algorithm. Wireless Interconnection Technology, 21, 119-122.

ABSTRACT: As a highly contagious respiratory disease, influenza exhibits significant spatiotemporal fluctuations in incidence, posing a persistent threat to public health and placing considerable ...
The New York Times

Andrew A. Beveridge, Who Found the Unexpected in Census Data, Dies at 79

With his own research group and as a professor at Queens College, he plumbed raw data for often-surprising insights about the way the country was changing. By Sam Roberts Andrew A. Beveridge, a ...
IEEE

A Topological-Indicators-Based k-Means Clustering Algorithm and Its Application in Time Series Data: A Case Study on Sea Level Variability in Peninsular Malaysia

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, ...
Frontiers

Spectral Clustering Algorithm for Cognitive Diagnostic Assessment

In cognitive diagnostic assessment (CDA), clustering analysis is an efficient approach to classify examinees into attribute-homogeneous groups. Many researchers have proposed different methods, such ...
IEEE

Data mining technique with cluster anaysis use K-means algorithm for LQ45 index on Indonesia stock exchange

Abstract: This study aims to apply data mining techniques with cluster analysis on stock data registered in LQ45 in Indonesia Stock Exchange. The cluster analysis used in this method is k-means ...