PSI - Issue 48

Oleh Yasniy et al. / Procedia Structural Integrity 48 (2023) 149–154 Yasniy et al/ Structural Integrity Procedia 00 (2023) 000–000

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Yasniy, P.V., Hlado, V.B., Fedak, S.I., Shulhan, I.V., 2010. Modelling of deformation of smooth specimen and specimen with crack at dynamic creep. International scientific and technical conference "Strength of materials and structural elements". Kyiv, Ukraine, 2014-2015. [in Ukrainian] Didych, I., Yasniy, O., Fedak, S., Lapusta, Yu., 2022. Prediction of jump-like creep using preliminary plastic strain. Procedia Structural Integrity 36, 166–170. Pidaparti, R. M. V., Palakal, M. J., 1995. Neural network approach to fatigue-crack-growth predictions under aircraft spectrum loadings. Journal of Aircraft 32, 825-831. Mohanty, J. R., Verma, B. B., Parhi, D. R. K., Ray D. R., 2009. Application of artificial neural network for predicting fatigue crack propagation life of aluminum alloys. Archives of Computational Materials Science and Surface Engineering 1, 133–138. Goodfellow, I., Bengio, Y., Courville, A.2016. Deep Learning, The MIT Press, pp. 800.

Haykin, S., 1999. Neural Networks: A Comprehensive Foundation. Second Ed., Prentice Hall, Canada, pp. 823. Alpayndin, E., 2010. Introduction to Machine Learning. The Knowledge Engineering Review 25, 353. Smola, A., Vishwanathan, S.V.N., 2010. Introduction to Machine Learning , Cambridge University Press, pp. 234. Gurney, K., 1997. An introduction to neural networks, First Ed., Taylor & Francis Group, London, pp. 317. Richard, D. N., 1998. Applied regression analysis, Third Ed., John Wiley & Sons, New York, pp. 736.

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