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Distance-based clustering and classification are widely used in various fields to group mixed numeric and categorical data. In many algorithms, a predefined distance measurement is used to cluster data points based on their dissimilarity.…

Machine Learning · Computer Science 2024-10-14 Jesse S. Ghashti , John R. J. Thompson

A framework of online adaptive statistical compressed sensing is introduced for signals following a mixture model. The scheme first uses non-adaptive measurements, from which an online decoding scheme estimates the model selection. As soon…

Computer Vision and Pattern Recognition · Computer Science 2011-12-30 Julio Duarte-Carvajalino , Guillermo Sapiro , Guoshen Yu , Lawrence Carin

Modern online mass spectrometry generates multi-terabyte data streams critical for understanding Earth's environmental systems. However, extracting actionable chemical insights from these repositories is impeded by a computational…

Machine Learning · Computer Science 2026-05-11 Shao Shi , Xin Yang , Huiran Feng , Jianhuai Ye , Tianlong Hu , Yaling Zeng , Tzung-May Fu , Lei Zhu , Huizhong Shen , Chen Wang , Shu Tao

In this paper, we propose a new measure for detecting overlap in multivariate Gaussian clusters. The aim of online learning from data streams is to create clustering, classification, or regression models that can adapt over time based on…

Machine Learning · Computer Science 2025-08-22 Miha Ožbot , Igor Škrjanc

Real-time tracking of inertia is important because it reflects the power system's ability to withstand contingencies and maintain frequency security. This paper proposes a practical approach to estimate inertia using ambient phasor…

Systems and Control · Electrical Eng. & Systems 2025-08-12 Anushka Sharma , Anamitra Pal , Rajasekhar Anguluri , Tamojit Chakraborty

Clustering algorithms are fundamental tools across many fields, with density-based methods offering particular advantages in identifying arbitrarily shaped clusters and handling noise. However, their effectiveness is often limited by the…

Machine Learning · Computer Science 2025-12-01 Meysam Shirdel Bilehsavar , Razieh Ghaedi , Samira Seyed Taheri , Xinqi Fan , Christian O'Reilly

Phasor measurement units (PMUs) have the advantage of providing direct measurements of power states. However, as the number of PMUs in a power system is limited, the traditional supervisory control and data acquisition (SCADA) system cannot…

Systems and Control · Computer Science 2016-07-12 Jian Du , Shaodan Ma , Yik-Chung Wu , H. Vincent Poor

Atom probe tomography is commonly used to study solute clustering and precipitation in materials. However, standard techniques, such as the density based spatial clustering applications with noise (DBSCAN) perform poorly with respect to…

Materials Science · Physics 2025-09-05 R S. Stroud , A. Al-Saffar , M. Carter , M P. Moody , S. Pedrazzini , M R. Wenman

DBSCAN is a typically used clustering algorithm due to its clustering ability for arbitrarily-shaped clusters and its robustness to outliers. Generally, the complexity of DBSCAN is O(n^2) in the worst case, and it practically becomes more…

Databases · Computer Science 2018-01-23 Thapana Boonchoo , Xiang Ao , Qing He

Integration of intermittent renewable energy sources in modern power systems is increasing very fast. Replacement of synchronous generators with zero-to-low variable renewables substantially decreases the system inertia. In a large system,…

Signal Processing · Electrical Eng. & Systems 2020-06-23 Mingjian Tuo , Xingpeng Li

The problem of effective use of Phasor Measurement Units (PMUs) to enhance power systems awareness and security is a topic of key interest. The central question to solve is how to use this new measurements to reconstruct the state of the…

Systems and Control · Electrical Eng. & Systems 2020-04-16 Alexey Bobtsov , Romeo Ortega , Nikolay Nikolaev , Johannes Schiffer , M. Nicolai L. Lorenz-Meyer

Phasor measurement units (PMUs) provide a high-resolution view of the power system at the locations where they are placed. As such, it is desirable to place them in bulk in low voltage distribution circuits. However, the power consumption…

Classically, Bayesian clustering interprets each component of a mixture model as a cluster. The inferred clustering posterior is highly sensitive to any inaccuracies in the kernel within each component. As this kernel is made more flexible,…

Methodology · Statistics 2025-12-12 David Buch , Miheer Dewaskar , David B. Dunson

The use of phasor angle measurements provided by phasor measurement units (PMUs) in fault detection is regarded as a promising method in identifying locations of power line outages. However, communication errors or system malfunctions may…

Systems and Control · Computer Science 2016-11-17 Wen-Tai Li , Chao-Kai Wen , Jung-Chieh Chen , Kai-Kit Wong , Jen-Hao Teng , Chau Yuen

Phasor Measurement Unit (PMU) technology is increasingly used for real-time monitoring applications, especially line outage detection and identification (D&I) in the power system. Current outage D&I schemes either assume a full PMU…

Systems and Control · Electrical Eng. & Systems 2020-09-08 Xiaozhou Yang , Nan Chen , Chao Zhai

DBSCAN has been widely used in density-based clustering algorithms. However, with the increasing demand for Multi-density clustering, previous traditional DSBCAN can not have good clustering results on Multi-density datasets. In order to…

Databases · Computer Science 2023-10-10 Ziqing Wang , Zhirong Ye , Yuyang Du , Yi Mao , Yanying Liu , Ziling Wu , Jun Wang

In 2016 the British government acknowledged the importance of reducing antimicrobial prescriptions in order to avoid the long-term harmful effects of over-prescription. Prescription needs are highly dependent on factors that have a…

Applications · Statistics 2021-09-14 Antonia Gieschen , Jake Ansell , Raffaella Calabrese , Belen Martin-Barragan

To improve the identification of potential anomaly patterns in complex user behavior, this paper proposes an anomaly detection method based on a deep mixture density network. The method constructs a Gaussian mixture model parameterized by a…

Machine Learning · Computer Science 2025-05-20 Lu Dai , Wenxuan Zhu , Xuehui Quan , Renzi Meng , Sheng Chai , Yichen Wang

This paper presents a comprehensive comparative analysis of prominent clustering algorithms K-means, DBSCAN, and Spectral Clustering on high-dimensional datasets. We introduce a novel evaluation framework that assesses clustering…

Machine Learning · Computer Science 2025-07-31 Vishnu Vardhan Baligodugula , Fathi Amsaad

Increased adoption and deployment of phasor measurement units (PMU) has provided valuable fine-grained data over the grid. Analysis over these data can provide insight into the health of the grid, thereby improving control over operations.…

Databases · Computer Science 2016-05-26 Ben McCamish , Rich Meier , Jordan Landford , Robert Bass , Eduardo Cotilla-Sanchez , David Chiu
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