Multi-Feature Extraction and Explainable Machine Learning for Lamb-Wave-Based Damage Localization in Laminated Composites
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Spyros Makridakis & Evangelos Spiliotis & Vassilios Assimakopoulos & Artemios-Anargyros Semenoglou & Gary Mulder & Konstantinos Nikolopoulos, 2023. "Statistical, machine learning and deep learning forecasting methods: Comparisons and ways forward," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 74(3), pages 840-859, March.
- Ebtisam AlJalaud & Manar Hosny, 2024. "Enhancing Explainable Artificial Intelligence: Using Adaptive Feature Weight Genetic Explanation (AFWGE) with Pearson Correlation to Identify Crucial Feature Groups," Mathematics, MDPI, vol. 12(23), pages 1-48, November.
- Nizar Faisal Alkayem & Ali Mayya & Lei Shen & Xin Zhang & Panagiotis G. Asteris & Qiang Wang & Maosen Cao, 2024. "Co-CrackSegment: A New Collaborative Deep Learning Framework for Pixel-Level Semantic Segmentation of Concrete Cracks," Mathematics, MDPI, vol. 12(19), pages 1-37, October.
- P. M. Lerman, 1980. "Fitting Segmented Regression Models by Grid Search," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(1), pages 77-84, March.
- Xi, Zhimin & Zhao, Xiangxue, 2019. "An enhanced copula-based method for data-driven prognostics considering insufficient training units," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 181-194.
- Ntzoufras, Ioannis, 2002. "Gibbs Variable Selection using BUGS," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i07).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Jiang, Deyin & Chen, Tianyu & Xie, Juanzhang & Cui, Weimin & Song, Bifeng, 2023. "A mechanical system reliability degradation analysis and remaining life estimation method——With the example of an aircraft hatch lock mechanism," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
- Fan, Xudong & Wang, Xiaowei & Zhang, Xijin & ASCE Xiong (Bill) Yu, P.E.F., 2022. "Machine learning based water pipe failure prediction: The effects of engineering, geology, climate and socio-economic factors," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
- Adham Alsharkawi & Mohammad Al-Fetyani & Maha Dawas & Heba Saadeh & Musa Alyaman, 2021. "Poverty Classification Using Machine Learning: The Case of Jordan," Sustainability, MDPI, vol. 13(3), pages 1-16, January.
- Ben Q. Liu & Dale L. Goodhue, 2012. "Two Worlds of Trust for Potential E-Commerce Users: Humans as Cognitive Misers," Information Systems Research, INFORMS, vol. 23(4), pages 1246-1262, December.
- Alnajjar, Khalid & Hämäläinen, Mika, 2024. "MLPESTEL: The New Era of Forecasting Change in the Operational Environment of Businesses Using LLMs," Thesis Commons qz8hk_v1, Center for Open Science.
- Chen Huann-Sheng & Zeichner Sarah & Anderson Robert N. & Espey David K. & Kim Hyune-Ju & Feuer Eric J., 2020. "The Joinpoint-Jump and Joinpoint-Comparability Ratio Model for Trend Analysis with Applications to Coding Changes in Health Statistics," Journal of Official Statistics, Sciendo, vol. 36(1), pages 49-62, March.
- Tan, Xiujie & Xiao, Ziwei & Liu, Yishuang & Taghizadeh-Hesary, Farhad & Wang, Banban & Dong, Hanmin, 2022. "The effect of green credit policy on energy efficiency: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
- Muñoz, J.F. & Arcos, A. & Álvarez, E. & Rueda, M., 2014. "New ratio and difference estimators of the finite population distribution function," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 102(C), pages 51-61.
- Suwon Song & Chun Gun Park, 2019. "Alternative Algorithm for Automatically Driving Best-Fit Building Energy Baseline Models Using a Data—Driven Grid Search," Sustainability, MDPI, vol. 11(24), pages 1-11, December.
- Yu, Binbing & Barrett, Michael J. & Kim, Hyune-Ju & Feuer, Eric J., 2007. "Estimating joinpoints in continuous time scale for multiple change-point models," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2420-2427, February.
- Tahira Kootbodien & Nisha Naicker & Kerry S. Wilson & Raj Ramesar & Leslie London, 2020. "Trends in Suicide Mortality in South Africa, 1997 to 2016," IJERPH, MDPI, vol. 17(6), pages 1-16, March.
- Jonathan Readshaw & Stefano Giani, 2020. "Using Company Specific Headlines and Convolutional Neural Networks to Predict Stock Fluctuations," Papers 2006.12426, arXiv.org.
- Erjia Ge & Yee Leung, 2013. "Detection of crossover time scales in multifractal detrended fluctuation analysis," Journal of Geographical Systems, Springer, vol. 15(2), pages 115-147, April.
- Liu, Xiang-dong & Pan, Fei & Cai, Wen-li & Peng, Rui, 2020. "Correlation and risk measurement modeling: A Markov-switching mixed Clayton copula approach," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
- Mohammadreza Mohebbi & Rory Wolfe & Andrew Forbes, 2014. "Disease Mapping and Regression with Count Data in the Presence of Overdispersion and Spatial Autocorrelation: A Bayesian Model Averaging Approach," IJERPH, MDPI, vol. 11(1), pages 1-20, January.
- Bucarey, Víctor & Labbé, Martine & Morales, Juan M. & Pineda, Salvador, 2021. "An exact dynamic programming approach to segmented isotonic regression," Omega, Elsevier, vol. 105(C).
- Niu, Tong & Li, Yu & Zhang, Caizhi & Hu, Xiaosong & Wang, Gucheng & Li, Yuehua & Zeng, Tao & Wei, Zhongbao, 2024. "Prediction of fuel cell degradation trends using long short term memory optimization algorithm based on four-module experimental reactor validation," Renewable Energy, Elsevier, vol. 237(PC).
- Chang, Mingu & Lee, Jongsoo, 2020. "Early stage data-based probabilistic wear life prediction and maintenance interval optimization of driving wheels," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
- Lutz Bornmann & Rüdiger Mutz, 2015. "Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(11), pages 2215-2222, November.
- Tenan, Simone & O’Hara, Robert B. & Hendriks, Iris & Tavecchia, Giacomo, 2014. "Bayesian model selection: The steepest mountain to climb," Ecological Modelling, Elsevier, vol. 283(C), pages 62-69.
More about this item
Keywords
Lamb wave; damage localization; explainable machine learning; SHAP; multi-feature extraction; K-Nearest Neighbor regressor; laminated composites;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:13:y:2025:i:5:p:769-:d:1600395. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.