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Hybrid physics-informed neural networks for main bearing fatigue prognosis with visual grease inspection., and . Comput. Ind., (2021)A Tutorial on Latin Hypercube Design of Experiments.. Qual. Reliab. Eng. Int., 32 (5): 1975-1985 (2016)Efficient global optimization algorithm assisted by multiple surrogate techniques., , and . J. Glob. Optim., 56 (2): 669-689 (2013)Can Ants Design Mechanical Engineering Systems?, , , and . IEEE Congress on Evolutionary Computation, page 831-837. IEEE, (2006)Physics-Informed Neural Networks for Missing Physics Estimation in Cumulative Damage Models: A Case Study in Corrosion Fatigue., and . J. Comput. Inf. Sci. Eng., (2020)Early life failures and services of industrial asset fleets., and . Reliab. Eng. Syst. Saf., (2021)Fleet Prognosis with Physics-informed Recurrent Neural Networks., and . CoRR, (2019)Optimization of aircraft structural components by using nature-inspired algorithms and multi-fidelity approximations., , , and . J. Glob. Optim., 45 (3): 427-449 (2009)A tutorial on solving ordinary differential equations using Python and hybrid physics-informed neural network., , and . Eng. Appl. Artif. Intell., (2020)Player Needs First: Understanding Player Needs Before Designing a K-pop Themed Mobile Game., and . HCI (1), volume 12181 of Lecture Notes in Computer Science, page 201-216. Springer, (2020)