Suchergebnisse - "Unsupervised data-driven method"

Unsupervised data-driven method for damage localization using guided waves von Lomazzi, Luca, Junges, Rafael, Giglio, Marco, Cadini, Francesco

“… Researchers have recently gained interest in ultrasonic guided waves (UGWs) for structural health monitoring (SHM). This interest has mainly grown thanks to …”
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A Novel Unsupervised Data-Driven Method for Electricity Theft Detection in AMI Using Observer Meters von Qi, Ruobin, Zheng, Jun, Luo, Zhirui, Li, Qingqing

“… A novel unsupervised data-driven method for electricity theft detection in AMI is proposed in this paper …”
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Seq-SVF: An unsupervised data-driven method for automatically identifying hidden governing equations von Wu, Zhetong, Ye, Hongfei, Zhang, Hongwu, Zheng, Yonggang

“… In this work, an unsupervised data-driven method based on sequential singular value filtering (Seq-SVF …”
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An unsupervised adversarial autoencoder for cyber attack detection in power distribution grids von Zideh, Mehdi Jabbari, Khalghani, Mohammad Reza, Solanki, Sarika Khushalani

“… Detection of cyber attacks in smart power distribution grids with unbalanced configurations poses challenges due to the inherent nonlinear nature of these …”
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Multivariate physics-informed convolutional autoencoder for anomaly detection in power distribution systems with widespread deployment of distributed energy resources von Jabbari Zideh, Mehdi, Khushalani Solanki, Sarika

“… Despite the relentless progress of deep learning models in analyzing the system conditions under cyber-physical events, their abilities are limited in the …”
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Data‐driven approaches for tau‐PET imaging biomarkers in Alzheimer's disease von Vogel, Jacob W., Mattsson, Niklas, Iturria‐Medina, Yasser, Strandberg, Olof T., Schöll, Michael, Dansereau, Christian, Villeneuve, Sylvia, Flier, Wiesje M., Scheltens, Philip, Bellec, Pierre, Evans, Alan C., Hansson, Oskar, Ossenkoppele, Rik

“… The present study employs an unsupervised data‐driven method to identify spatial patterns of tau …”
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Characterizing symptom clusters for older adults with urinary incontinence in home healthcare von Scharp, Danielle, Song, Jiyoun, Xu, Zidu, Palmer, Mary Happel, Barcelona, Veronica, Topaz, Maxim

“… We employed hierarchical clustering, an unsupervised, data-driven method that iteratively identifies naturally occurring symptom subgroups without constraining the number of symptoms required …”
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Unsupervised separation of the thermosensitive contribution in the power consumption at a country scale von Dampeyrou, Charles, Goichon, Antoine, Ghienne, Martin, Tschannen, Valentin, Schaack, Sofiane

“… This paper presents a “by-design” unsupervised data-driven method to separate the consumptions due to the weather in the overall electricity consumption …”
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Physics-Informed Convolutional Autoencoder for Cyber Anomaly Detection in Power Distribution Grids von Zideh, Mehdi Jabbari, Solanki, Sarika Khushalani

“… The growing trend toward the modernization of power distribution systems has facilitated the installation of advanced measurement units and promotion of the …”
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Massive modulation of brain areas after mechanical pain stimulation: a time-resolved FMRI study von Cauda, Franco, Costa, Tommaso, Diano, Matteo, Sacco, Katiuscia, Duca, Sergio, Geminiani, Giuliano, Torta, Diana M E

“… To avoid any assumption about the shape of BOLD response, we used an unsupervised data-driven method to group voxels sharing a time course similar to the BOLD response to the stimulus and found …”
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Bayesian Geometric-based Interactions Learning Model for Self-aware Autonomous Agents von Iqbal, Hafsa, Marin, Pablo, Marcenaro, Lucio, Gomez, David Martin, Regazzioni, Carlo

“… Autonomous agents can perceive and act in the environment only by interacting with neighboring agents. This paper proposes a novel probabilistic interaction …”
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Multimodal manifold learning using kernel interpolation along geodesic paths von Katz, Ori, Lederman, Roy R., Talmon, Ronen

“… In this paper, we present a new spectral analysis and a low-dimensional embedding of two aligned multimodal datasets. Our approach combines manifold learning …”
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A Data-Driven Method Based on Bidirectional Convolutional Current Neural Network to Detect Structural Damage von Xue, Songling, Su, Teng, Xie, Qinghai, Zhao, Xiaoqing, Zong, Zhongling

“… In addressing the challenge of lacking precise mathematical and mechanical models, as well as data labels in structural damage identification, this paper …”
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A hybrid-based clustering algorithm for targeting porphyry copper mineralization at Chahargonbad district in SE Iran von Hossein Rahimi, Maysam Abedi, Abbas Bahroudi, Mohammad Javad Rezapour, Gholam-Reza Elyasi, Soheila Aslani

“… This work presents a hybrid-based clustering approach for mineral potential mapping (MPM) of porphyry-type Cu mineralization at Kerman province in the SE of …”
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Longitudinal trajectories of asthma exacerbations from infancy to school age von Deliu, Matea

“… of the heterogeneity of asthma syndrome. We used longitudinal k-means modelling (an unsupervised data-driven method …”
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A CUSUM-based condition monitoring algorithm for power electronics based on SOM-MQE feature extraction method von Yang, Qian, Joshi, Shailesh, Ukegawa, Hiroshi, Viviano, Raymond, Pattipati, Krishna R.

“… This paper presents an unsupervised data-driven method that involves a distance-based feature extraction and the Page's Cumulative sum (CUSUM …”
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Data Driven Methods for Electricity Theft Detection in Advanced Metering Infrastructure von Qi, Ruobin

“… The Advanced Metering Infrastructure (AMI) is a critical component of modern smart grids, collecting vast amounts of high-frequency power consumption data from …”
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MASK+: Data-driven regions selection for acoustic fingerprinting von Ondel, Lucas, Anguera, Xavier, Luque, Jordi

“… Acoustic fingerprinting is the process to deterministically obtain a compact representation of an audio segment, used to compare multiple audio files or to …”
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Dust Deposition Diagnosis of Photovoltaic Modules Using Similarity-Based Modeling (SBM) Approach von Wang, Zhonghao, Xu, Zhengguo

“… An unsupervised data-driven method called Similarity-Based Modeling (SBM) was used to deal with this problem and some improvements of this method were adopted …”
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A framework for unsupervised fault detection and diagnosis based on clustering assisted kriging observer von Ardakani, Mohammad Hamed, Shokry, Ahmed, Escudero, Gerard, Graells, Moises, Espuna, Antonio

“… This paper presents an unsupervised data-driven method for Fault Detection and Diagnosis (FDD …”
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