Web Design System Based on Neural Networks for Strength and Mixing Proportion Prediction of RAC

Abstract

Recently, as construction wastes have increased and natural aggregates have lacked, it has largely studied about recycled aggregate which reuses of waste concrete. However, it is not enough to apply or practice recycled aggregate concrete for structural object. It is reason that the development of compressive strength is less than that of normal concrete in the concrete made with recycled aggregates due to the characteristic of recycled aggregate. Moreover, in spite of recognizing the difference between recycled aggregate and natural aggregate, the existing mix proportion for normal concrete has been applied to mix proportion of concrete made with recycled aggregate. The purpose of this research is to develop ”Web-Based Prediction System for Recycled Aggregate Concrete” that provides an accurate prediction values of compressive strength and mixing proportion on the recycled aggregate concrete under characteristic of recycled aggregate.