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Macrostate Data Clustering [PDF]
Physical Review E, 2003 We develop an effective nonhierarchical data clustering method using an analogy to the dynamic coarse graining of a stochastic system. Analyzing the eigensystem of an interitem transition matrix identifies fuzzy clusters corresponding to the metastable ...
A. Pothen +17 more
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Generative Adversarial Networks and Data Clustering for Likable Drone Design [PDF]
Sensors, 2022 Novel applications for human-drone interaction demand new design approaches, such as social drones that need to be perceived as likable by users. However, given the complexity of the likability perception process, gathering such design information from ...
Lee J. Yamin, Jessica R. Cauchard
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Urban Road Surface Discrimination by Tire-Road Noise Analysis and Data Clustering [PDF]
Sensors, 2022 The surface condition of roadways has direct consequences on a wide range of processes related to the transportation technology, quality of road facilities, road safety, and traffic noise emissions.
Carlos Ramos-Romero +3 more
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Spectral Clustering with Imbalanced Data [PDF]
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013 Spectral clustering is sensitive to how graphs are constructed from data particularly when proximal and imbalanced clusters are present. We show that Ratio-Cut (RCut) or normalized cut (NCut) objectives are not tailored to imbalanced data since they tend
Qian, Jing, Saligrama, Venkatesh
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Data Clustering Using Moth-Flame Optimization Algorithm [PDF]
Sensors, 2021 A k-means algorithm is a method for clustering that has already gained a wide range of acceptability. However, its performance extremely depends on the opening cluster centers.
Tribhuvan Singh +5 more
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Evaluating Clustering Algorithms: An Analysis using the EDAS Method [PDF]
E3S Web of Conferences, 2023 Data clustering is frequently utilized in the early stages of analyzing big data. It enables the examination of massive datasets encompassing diverse types of data, with the aim of revealing undiscovered correlations, concealed patterns, and other ...
Siva Shankar S. +3 more
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Известия высших учебных заведений России: Радиоэлектроника, 2021 Introduction. Requirements for the quality of information about the trajectory of moving objects provided by sensor networks are increasingly becoming more stringent.
Nguyen Phung Bao, Quang Hieu Dang
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Известия высших учебных заведений и энергетических объединенний СНГ: Энергетика, 2023 Renewable energy sources (RES) are seen as a means of the fuel and energy complex carbon footprint reduction but the stochastic nature of generation complicates RES integration with electric power systems.
P. V. Matrenin +6 more
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Investigation the motion data clustering of lung tumor on its position estimation at external surrogates’ radiotherapy [PDF]
مجله مدل سازی در مهندسی, 2022 Among thorax tumors, lung tumors move mainly due to respiration. In order to enhance the precision of radiotherapy, one solution is estimating tumor motion from external motion of chest wall and abdomen regions. For this aim, consistent prediction models
Ahmad Esmaili Torshabi
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Lithofacies Identification from Wire-Line Logs Using an Unsupervised Data Clustering Algorithm
Energies, 2023 Stratigraphic identification from wire-line logs and core samples is a common method for lithology classification. This traditional approach is considered superior, despite its significant financial cost.
Md Monjur Ul Hasan +5 more
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