Prediction of concrete strength using artificial neural networks

By Seung-Chang Lee. 2003

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Prediction of self-compacting concrete strength using artificial neural networks (2016, methodology): “Lee, S. C. (2003). Prediction of concrete strength using artificial neural networks. Engineering Structures, 25, 849–857. Lourakis, M. I. A. (2005). A brief description of the Levenberg-Marquardt algorithm Implemened by levmar.”
Prediction of the strength of mineral admixture concrete using multivariable regression analysis and an artificial neural network (2011, background): “AnANNcancontinuously re-train thenew data,meaning that it can conveniently adapt tonewdata (Lee, 2003).”
Non-linear and mixed regression models in predicting sustainable concrete strength (2018, methodology): “672 143 In literature review, ANN was found to be the most widely used modeling approach in 144 predicting concrete properties [18, 28, 31, 32, 33, 34, 35, 36].”
Computational design optimization of concrete mixtures: A review (2018, neutral): “These decision variables were grouped into four categories: material proportions, basic information, measurement variables, and temperature and humidity history of the pour [48].”