Search Results - Unsupervised data-driven method

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  1. 1

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

    ISSN: 0888-3270
    Published: Elsevier Ltd 15.02.2024
    Published in Mechanical systems and signal processing (15.02.2024)
    “… To date, localization has been mainly performed through tomographic algorithms. Although those algorithms represent consolidated methods, they come with unsolved…”
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    Journal Article
  2. 2

    A Novel Unsupervised Data-Driven Method for Electricity Theft Detection in AMI Using Observer Meters by Qi, Ruobin, Zheng, Jun, Luo, Zhirui, Li, Qingqing

    ISSN: 0018-9456, 1557-9662
    Published: New York IEEE 2022
    “… A novel unsupervised data-driven method for electricity theft detection in AMI is proposed in this paper…”
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    Journal Article
  3. 3

    Seq-SVF: An unsupervised data-driven method for automatically identifying hidden governing equations by Wu, Zhetong, Ye, Hongfei, Zhang, Hongwu, Zheng, Yonggang

    ISSN: 0010-4655, 1879-2944
    Published: Elsevier B.V 01.11.2023
    Published in Computer physics communications (01.11.2023)
    “…In this work, an unsupervised data-driven method based on sequential singular value filtering (Seq-SVF…”
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    Journal Article
  4. 4

    Unsupervised Learning Methods for Data-Driven Vibration-Based Structural Health Monitoring: A Review by Eltouny, Kareem, Gomaa, Mohamed, Liang, Xiao

    ISSN: 1424-8220, 1424-8220
    Published: Switzerland MDPI AG 20.03.2023
    Published in Sensors (Basel, Switzerland) (20.03.2023)
    “… In this article, we review publications on data-driven structural health monitoring from the last decade that relies on unsupervised learning methods with a focus on real-world application and practicality…”
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    Journal Article
  5. 5

    An unsupervised adversarial autoencoder for cyber attack detection in power distribution grids by Zideh, Mehdi Jabbari, Khalghani, Mohammad Reza, Solanki, Sarika Khushalani

    ISSN: 0378-7796, 1873-2046
    Published: Elsevier B.V 01.07.2024
    Published in Electric power systems research (01.07.2024)
    “… To address these challenges, this paper proposes an unsupervised adversarial autoencoder (AAE) model to detect FDIAs in unbalanced…”
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    Journal Article
  6. 6

    A data-driven method for unsupervised electricity consumption characterisation at the district level and beyond by Mor, Gerard, Cipriano, Jordi, Martirano, Giacomo, Pignatelli, Francesco, Lodi, Chiara, Lazzari, Florencia, Grillone, Benedetto, Chemisana, Daniel

    ISSN: 2352-4847, 2352-4847
    Published: Elsevier Ltd 01.11.2021
    Published in Energy reports (01.11.2021)
    “…A bottom-up electricity characterisation methodology of the building stock at the local level is presented. It is based on the statistical learning analysis of…”
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    Journal Article
  7. 7
  8. 8

    An unsupervised data completion method for physically-based data-driven models by Ayensa-Jiménez, Jacobo, Doweidar, Mohamed H., Sanz-Herrera, Jose A., Doblaré, Manuel

    ISSN: 0045-7825, 1879-2138
    Published: Amsterdam Elsevier B.V 01.02.2019
    “…Data-driven methods are an innovative model-free approach for engineering and sciences, still in process of maturation…”
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    Journal Article
  9. 9

    Multivariate physics-informed convolutional autoencoder for anomaly detection in power distribution systems with widespread deployment of distributed energy resources by Jabbari Zideh, Mehdi, Khushalani Solanki, Sarika

    ISSN: 2352-4677, 2352-4677
    Published: Elsevier Ltd 01.12.2025
    Published in Sustainable Energy, Grids and Networks (01.12.2025)
    “…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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    Journal Article
  10. 10

    A data-driven air quality assessment method based on unsupervised machine learning and median statistical analysis: The case of China by Wang, Xiaoxia, Wang, Luqi, Liu, Yuanyuan, Hu, Sangen, Liu, Xuezhen, Dong, Zhongzhen

    ISSN: 0959-6526, 1879-1786
    Published: Elsevier Ltd 15.12.2021
    Published in Journal of cleaner production (15.12.2021)
    “… Unsupervised machine learning was applied to classify 367 cities across China into seven categories…”
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    Journal Article
  11. 11

    An Unsupervised Feature Selection Method for Data-Driven Anomaly Detection Systems by Almusallam, Naif

    ISSN: 2641-8169
    Published: IEEE 01.09.2020
    “…Feature selection has been widely used as a pre-processing step that helps to optimise the performance of data-driven intrusion/anomaly detection systems in achieving their tasks…”
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    Conference Proceeding
  12. 12

    Physics-Informed Convolutional Autoencoder for Cyber Anomaly Detection in Power Distribution Grids by Zideh, Mehdi Jabbari, Solanki, Sarika Khushalani

    ISSN: 1944-9933
    Published: IEEE 21.07.2024
    “… However, these infrastructures are still prone to stealth cyber attacks. The existing data-driven anomaly detection methods suffer from a lack of knowledge…”
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    Conference Proceeding
  13. 13

    An unsupervised data-driven approach for behind-the-meter photovoltaic power generation disaggregation by Pan, Keda, Chen, Zhaohua, Lai, Chun Sing, Xie, Changhong, Wang, Dongxiao, Li, Xuecong, Zhao, Zhuoli, Tong, Ning, Lai, Loi Lei

    ISSN: 0306-2619, 1872-9118
    Published: Elsevier Ltd 01.03.2022
    Published in Applied energy (01.03.2022)
    “…•Proposed an unsupervised BtM PVPG disaggregation method with data-driven approach…”
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    Journal Article
  14. 14

    An Evaluation Method for Pavement Maintenance Priority Classification Based on an Unsupervised Data-Driven Multidimensional Performance Model by Zhao, Jing, Wang, Xuancang, Wang, Shuai, Guo, Yucheng, Ji, Guanyu, Li, Shanqiang

    ISSN: 2193-567X, 1319-8025, 2191-4281
    Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2022
    “… This paper proposes an unsupervised multidimensional performance data-driven model for evaluating road maintenance priority based on comprehensive multidimensional indicators, which solves the issues…”
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    Journal Article
  15. 15

    A Review on DataDriven Learning Approaches for Fault Detection and Diagnosis in Chemical Processes by Taqvi, Syed Ali Ammar, Zabiri, Haslinda, Tufa, Lemma Dendena, Uddin, Fahim, Fatima, Syeda Anmol, Maulud, Abdulhalim Shah

    ISSN: 2196-9744, 2196-9744
    Published: 01.06.2021
    Published in ChemBioEng reviews (01.06.2021)
    “… Methods based on supervised and unsupervised datadriven techniques are reviewed, and the challenges in the field of fault detection and diagnosis have also been highlighted…”
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    Journal Article
  16. 16

    Datadriven approaches for tau‐PET imaging biomarkers in Alzheimer's disease by 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

    ISSN: 1065-9471, 1097-0193, 1097-0193
    Published: Hoboken, USA John Wiley & Sons, Inc 01.02.2019
    Published in Human brain mapping (01.02.2019)
    “… The present study employs an unsupervised datadriven method to identify spatial patterns of tau…”
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    Journal Article
  17. 17

    A Systematic Review of Studies Reporting Data-Driven Cognitive Subtypes across the Psychosis Spectrum by Green, Melissa J., Girshkin, Leah, Kremerskothen, Kyle, Watkeys, Oliver, Quidé, Yann

    ISSN: 1040-7308, 1573-6660, 1573-6660
    Published: New York Springer US 01.12.2020
    Published in Neuropsychology review (01.12.2020)
    “… We systematically reviewed the evidence from published studies reporting the use of data-driven (i.e., unsupervised) clustering methods to delineate cognitive subtypes among adults diagnosed with schizophrenia, schizoaffective disorder, or bipolar disorder…”
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    Journal Article
  18. 18

    Unsupervised machine and deep learning methods for structural damage detection: A comparative study by Wang, Zilong, Cha, Young‐Jin

    ISSN: 2577-8196, 2577-8196
    Published: Hoboken, USA John Wiley & Sons, Inc 01.01.2025
    Published in Engineering reports (Hoboken, N.J.) (01.01.2025)
    “…‐driven methods in unsupervised learning mode have been developed to solve the practical difficulties in data acquisition for civil infrastructures in different scenarios…”
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    Journal Article
  19. 19

    Fault detection and diagnosis of large-scale HVAC systems in buildings using data-driven methods: A comprehensive review by Mirnaghi, Maryam Sadat, Haghighat, Fariborz

    ISSN: 0378-7788, 1872-6178
    Published: Lausanne Elsevier B.V 15.12.2020
    Published in Energy and buildings (15.12.2020)
    “…•Reviewing limitations of previous data-mining based FDD methods on HVAC systems…”
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    Journal Article
  20. 20

    Data-driven unsupervised anomaly detection and recovery of unmanned aerial vehicle flight data based on spatiotemporal correlation by Yang, Lei, Li, ShaoBo, Li, ChuanJiang, Zhu, CaiChao, Zhang, AnSi, Liang, GuoQiang

    ISSN: 1674-7321, 1869-1900
    Published: Beijing Science China Press 01.05.2023
    Published in Science China. Technological sciences (01.05.2023)
    “…) neural network data-driven method for unsupervised anomaly detection and recovery of UAV flight…”
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    Journal Article