A hybrid artificial neural network (ANN) coupled with response surface methodology (RSM) was trained and employed to predict the flexural strength of coal waste-treated concrete. The flexural strength of a large number of mixture designs was evaluated to create an experimental database. In this study, coal waste was used as a recycled additive in concrete. Computational intelligence can offer an eco-friendly alternative with superior accuracy and performance. Developing concrete mixture designs that meet project specifications is time-consuming, costly, and requires many trial batches and destructive tests that lead to material wastage. Construction activities have been a primary cause for depleting natural resources and are associated with stern environmental impact.
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