Search Results - Unsupervised data-driven method

Disaggregate travel demand analysis using big data sources: unsupervised learning methods for data-driven trip purpose estimation

Authors: Pierluigi Coppola Fulvio Silvestri Francesco De Fabiis et al.

Source: Transportation Research Procedia. 82:1824-1838

Unsupervised Underwater Image Enhancement Method Based on Data-Driven and Atmospheric Light Optimization

Authors: Jian Chang Zijian Wang Haibo Jin

Source: 2024 IEEE 2nd International Conference on Sensors, Electronics and Computer Engineering (ICSECE). :1-6

Data-Driven Model for PV Power Generation Patterns Extraction via Unsupervised Machine Learning Methods

Authors: Miraftabzadeh S. Longo M. Brenna M. et al.

Source: 2022 North American Power Symposium (NAPS). :1-5

Subject Terms: Photovoltaic generation, Pattern extraction, Singular value decomposition, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, K-means algorithm, Unsupervised machine learning

A new adaptable data-driven model approach for applying predictive maintenance in industrial systems through confidence sphere and the HMM-SVM method

Authors: Alexandre Martins João Rodrigues Balduíno Mateus et al.

Source: Results in Engineering, Vol 28, Iss , Pp 108131- (2025)

Subject Terms: Predictive maintenance, Industrial sensors, Unsupervised learning, Supervise learning, Confidence sphere, Machine learning, Technology

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2590123025041775; https://doaj.org/toc/2590-1230

Access URL: https://doaj.org/article/daaf383c981a4a44ba0b8c832cf90683

Harnessing the power of intersection for data disaggregation : a novel similarity measure and unsupervised data-driven classification method applied to financial contagion

Authors: Ferreira Cardia Haddad, Michel Arestis, Philip

Contributors: Ferreira Cardia Haddad, Michel Arestis, Philip

Subject Terms: 332, Similarity measure, Unsupervised classification, Cluster analysis, Nonparametric methods, Financial contagion, Portfolio diversification

Access URL: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.805927

DANSE: Data-Driven Non-Linear State Estimation of Model-Free Process in Unsupervised Learning Setup

Authors: Ghosh, Anubhab Honore, Antoine Chatterjee, Saikat

Source: IEEE Transactions on Signal Processing. 72:1824-1838

Subject Terms: State estimation, Computational modeling, Training, Bayes methods, Noise measurement, Supervised learning, Unsupervised learning, Bayesian state estimation, forecasting, neural networks, recurrent neural networks

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-346102

A Data-Driven Method for Water Quality Analysis and Prediction for Localized Irrigation

Authors: Roberto Fray da Silva Marcos Roberto Benso Fernando Elias Corrêa et al.

Source: AgriEngineering, Vol 6, Iss 2, Pp 1771-1793 (2024)

Subject Terms: 2. Zero hunger, Agriculture (General), 0207 environmental engineering, 02 engineering and technology, 15. Life on land, unsupervised learning, Engineering (General). Civil engineering (General), water quality, 01 natural sciences, 6. Clean water, S1-972, case study, 13. Climate action, water monitoring, 14. Life underwater, TA1-2040, data-driven methodology, clustering, 0105 earth and related environmental sciences

Access URL: https://doaj.org/article/d303dc7c24894502b0657c296899d14f

Unsupervised Real Time and Early Anomalies Detection Method for Sewer Networks Systems

Authors: Chunming Qiu Guoxiang Shao Zhenyu Zhang et al.

Source: IEEE Access, Vol 12, Pp 21698-21709 (2024)

Subject Terms: early warning, sewer networks, 13. Climate action, data-driven, 0211 other engineering and technologies, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, bagging, anomaly detection, 6. Clean water, Unsupervised, TK1-9971

Access URL: https://doaj.org/article/eaaf05fbf9d041a183b337f2ced1bfdc

A data-driven method for unsupervised electricity consumption characterisation at the district level and beyond

Authors: Gerard Mor Jordi Cipriano Giacomo Martirano et al.

Source: Repositorio Abierto de la UdL
Universitad de Lleida
Repositori Obert UdL
instname
RIARTE
Consejo General de la Arquitectura Técnica de España (CGATE)
Energy Reports, Vol 7, Iss, Pp 5667-5684 (2021)

Subject Terms: Consumo energético, Building-stock models, 0211 other engineering and technologies, 2202.03 Electricidad, 02 engineering and technology, 7. Clean energy, 3311.06 Instrumentos Eléctricos, Key Performance Indicators (KPIs), Electricity, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Edificación residencial, 1203.26 Simulación, Geolocalización, Characterisation, Building-stockmodels, Simulación energética - herramientas, Data-driven, Caracterización energética, TK1-9971, Comportamiento energético, 3305.14 Viviendas, General Energy, 2202.02 Magnitudes Eléctricas y Su Medida, 3311.02 Ingeniería de Control, 13. Climate action, Electrical engineering. Electronics. Nuclear engineering, Clima, Electricidad

Access URL: https://repositori.udl.cat/bitstream/10459.1/72061/1/enereo_a2021v7p5667.pdf
http://hdl.handle.net/10459.1/72061
https://doi.org/10.1016/j.egyr.2021.08.195
http://hdl.handle.net/20.500.12251/2467
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119584442&doi=10.1016/j.egyr.2021.08.195&partnerID=40&md5=9409121f289ec81fe0b89496a2093245
https://doaj.org/article/70d7ff0d26ce47269a32fe45dde904cb
https://www.scipedia.com/public/paper_Mor_Martinez_2021a
https://www.sciencedirect.com/science/article/pii/S2352484721007988
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3873133
https://www.openaccessrepository.it/record/156268

An Evaluation Method for Pavement Maintenance Priority Classification Based on an Unsupervised Data-Driven Multidimensional Performance Model

Authors: Jing Zhao Xuancang Wang Shuai Wang et al.

Source: Arabian Journal for Science and Engineering. 47:13265-13278

Subject Terms: 0211 other engineering and technologies, 02 engineering and technology

An unsupervised data completion method for physically-based data-driven models

Authors: Jacobo Ayensa-Jiménez Mohamed H. Doweidar Jose A. Sanz-Herrera et al.

Contributors: Jacobo Ayensa-Jiménez Mohamed H. Doweidar Jose A. Sanz-Herrera et al.

Source: idUS. Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname
Universidad de Zaragoza

Subject Terms: Computational mechanics, Data-driven methods, 0211 other engineering and technologies, 02 engineering and technology, 0101 mathematics, Statistical imputation, Data completion, 01 natural sciences, Weighted mean

File Description: application/pdf

Access URL: https://zaguan.unizar.es/record/84191/files/texto_completo.pdf
https://hdl.handle.net/11441/153938
http://zaguan.unizar.es/record/84191
https://www.sciencedirect.com/science/article/pii/S0045782518304882
https://ui.adsabs.harvard.edu/abs/2019CMAME.344..120A/abstract
https://idus.us.es/handle//11441/153938

A Novel Unsupervised Data-Driven Method for Electricity Theft Detection in AMI Using Observer Meters

Authors: Ruobin Qi Jun Zheng Zhirui Luo et al.

Source: IEEE Transactions on Instrumentation and Measurement. 71:1-10

Subject Terms: 0203 mechanical engineering, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Explainable sequential unsupervised data driven clustering for feature identification in external flows

Authors: D'Afiero, Francesco Mario

Source: Physics of fluids. 37(2)

File Description: print

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-360905
https://doi.org/10.1063/5.0257436

An Unsupervised Data-driven Method to Discover Equivalent Relations in Large Linked Datasets

Authors: Zhang, Ziqi Gentile, Anna Lisa Blomqvist, Eva et al.

Source: Semantic Web. 8(2)

Subject Terms: ontology alignment, ontology mapping, Linked Data, DBpedia, similarity measure

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-136222
https://liu.diva-portal.org/smash/get/diva2:1086233/FULLTEXT01.pdf

An interpretable unsupervised fault diagnosis method for rolling bearings based on physically-informed pseudo-label updating

Authors: Shijing Cao Yuxin Duan Jin Huang

Source: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. 239:8055-8072

An Unsupervised Feature Selection Method for Data-Driven Anomaly Detection Systems

Authors: Naif Almusallam

Source: 2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE). :36-41

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://dblp.uni-trier.de/db/conf/wetice/wetice2020.html#Almusallam20

A data-driven early warning method for thermal runaway of energy storage batteries and its application in retired lithium batteries

Authors: Fuxin Chen Xiaolin Chen Junwu Jin et al.

Source: Frontiers in Energy Research, Vol 11 (2024)

Subject Terms: energy storage battery, thermal runaway warning, 02 engineering and technology, unsupervised learning, 0210 nano-technology, 7. Clean energy, 01 natural sciences, General Works, data-driven method, retired lithium batteries, 0104 chemical sciences

Access URL: https://doaj.org/article/4770c0ca225643aaa0cafc31208a7f1a

Unsupervised Data-Driven Methods for Damage Identification in Discontinuous Media

Authors: Wesley F. Reinhart Branko Glisic Rebecca Napolitano

Source: Structural Integrity ISBN: 9783030817152

Access URL: https://collaborate.princeton.edu/en/publications/unsupervised-data-driven-methods-for-damage-identification-in-dis
https://www.researchwithnj.com/en/publications/unsupervised-data-driven-methods-for-damage-identification-in-dis
https://link.springer.com/chapter/10.1007/978-3-030-81716-9_10
https://pennstate.pure.elsevier.com/en/publications/unsupervised-data-driven-methods-for-damage-identification-in-dis

On an unsupervised method for parameter selection for the elastic net

Authors: Kereta, Zeljko Naumova, Valeriya

Source: Mathematics in Engineering, Vol 4, Iss 6, Pp 1-36 (2022)

Subject Terms: T57-57.97, Applied mathematics. Quantitative methods, iterative thresholding, parameter selection, 0101 mathematics, data-driven regularization, sub-gaussian vectors, matrix concentration inequalities, 01 natural sciences, elastic net regularization

Access URL: https://doaj.org/article/1f9693da41994289ab09204be698affb
http://www.aimspress.com/article/doi/10.3934/mine.2022053?viewType=html
https://discovery-pp.ucl.ac.uk/id/eprint/10173716/

Unsupervised Learning Methods for Data-Driven Vibration-Based Structural Health Monitoring: A Review

Authors: Kareem Eltouny Mohamed Gomaa Xiao Liang

Source: Sensors, Vol 23, Iss 6, p 3290 (2023)

Subject Terms: machine learning, deep learning, structural health monitoring, damage detection, unsupervised learning, novelty detection, Chemical technology, TP1-1185

File Description: electronic resource

Relation: https://www.mdpi.com/1424-8220/23/6/3290; https://doaj.org/toc/1424-8220

Access URL: https://doaj.org/article/d8a5bbbcaeac4ee9a0b264813da82595