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| Fatigue Damage Estimation of Wide Band Spectrum Considering Various Artificial Neural Networks |
| Jun-Bum Park, Sung-Yong Kim |
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J. Ocean Eng. Technol.. 2016;30(5):341-348. Published online October 31, 2016 DOI: https://doi.org/10.5574/KSOE.2016.30.5.341 |
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A METHOD OF SPATIAL SPECTRUM ESTIMATION USING NEURAL NETWORKS Artificial Neural Networks. 1991;1633-1636  Wide-banded fatigue damage evaluation of Catenary mooring lines using various Artificial Neural Networks models Marine Structures. 2018;60:186-200 Artificial neural networks in spectrum fatigue life prediction of composite materials International Journal of Fatigue. 2007;29(1):20-29 Deep and Wide Neural Networks Covariance Estimation Lecture Notes in Computer Science. 2020;195-206 An Artificial Neural Network-Based Algorithm for Evaluation of Fatigue Crack Propagation Considering Nonlinear Damage Accumulation Materials. 2016;9(6):483 Artificial neural network based breakwater damage estimation considering tidal level variation Ocean Engineering. 2014;87:185-190 Estimation of fatigue life for aluminium welded joints with the application of artificial neural networks Materialwissenschaft und Werkstofftechnik. 2011;42(10):888-893 GAMMA-BAND AND BETA-BAND CORTICAL OSCILLATIONS Artificial Neural Networks. 1992;847-850 Fatigue damage effect approach by artificial neural network International Journal of Fatigue. 2019;124:42-47 A Combination of Constitutive Damage Model and Artificial Neural Networks to Characterize the Mechanical Properties of the Healthy and Atherosclerotic Human Coronary Arteries Artificial Organs. 2017;41(9):E103-E117 |
