In this paper, a clustering method for KMedoids based on dynamic time warping (DTW-
KMedoids) is designed to analyze multi-channel signals, and a lightweight network …

Diversity and quality are two important factors that affect clustering ensemble performance.
Some base clusterings are irrelevant and redundant, which decreases the performance of …

聚类分析作为数据研究领域的基本技术, 旨在从无标签数据集中发现有意义的簇结构.
由Kleinberg 定理可知不存在能够学习任何数据集的基本聚类算法, 即没有一种聚类方法能够 …

In the era of expanding cloud-edge online service systems, predictive maintenance (PdM)
based on Key Performance Indicators (KPIs), such as CPU utilization, response rate, and …

Automatic clustering for seasonal time series based on entropy is a tool developed to
understand decision-making behaviours for economic agents. An unsupervised learning …

This paper explores a novel methodological area of ensemble clustering for financial time
series analysis, which aims to improve the stability, accuracy, and resilience of clustering …

Cette thèse s' inscrit dans le contexte du projet e-Gait dont l'objectif est de développer un
nouvel outil de mesure basé sur l'utilisation de systèmes numériques pour quantifier les …