Prediction of Concrete Compressive Strength Using Artificial Neural Network

Concrete is the most widely used material by humans after water. Rapid growth in construction industry, concrete will continue to be dominant future. a composite like aggregates, water, and admixtures. Destructive testing of know its strength achieved mix design an expensive time-consuming process. With recent advances soft computing techniques artificial intelligence, these results can predicted feeding algorithm with large number data available obtain desired results. In present research work, it proposed use neural networks predict different types concrete. A Multilayer Perceptron has input output layers, one or more hidden layers many neurons stacked together. Data capturing done regarding are preliminarily trained various inputs solve problems applica- ble This ANN captured helps minimizing repetitive process tests involved through experimental procedures which time, material, money- consuming practical difficulties. The advantage python that designer create customized program for interactive design, Python determination also improve analytical skill student programs converted into executable software. Cubes cast validate Result Software.