Smart Tech Predicts Green Building Material Strength

The building industry is going green, and recycled cement mortar (RCM) is getting attention. It's eco-friendly, but how strong is it? That's where smart tech comes in. Scientists used artificial neural networks (ANNs) to predict the strength of RCM. They added some smart algorithms to make the ANNs even better. These algorithms are like coaches, helping the ANNs perform at their best. The coaches used here were the grey wolf optimizer (GWO), particle swarm optimization (PSO), and genetic algorithm (GA). The team gathered data on RCM. They looked at things like the water-cement ratio, cement-sand ratio, and how much fly ash was used. They also considered how much recycled stuff was in the mix and how long it was left to dry. They even compared different amounts of data to see if it made a difference.The results? The ANNs with the smart coaches did a great job predicting strength. The PSO-ANN model was the star, with the best scores. It showed that the water-cement ratio, cement-sand ratio, and drying time were the most important factors. Interestingly, the amount of data didn't slow down the models. It was the complexity of the smart coaches that took more time. This study shows that smart tech can help design better, greener building materials. But here's a thought: while this tech is promising, it's important to remember that real-world conditions can be messy. The models might not always be perfect. Still, it's a step forward in making construction more sustainable.