A Study of Flexible Pavement with Replacement of Bitumen with Melted Tyres& Recycled Aggregates using ANN Technique

Abstract

Abstract Artificial neural network is a data processing mathematical model based on biological neurons. It is a complex structure composed of interconnected neurons that can be used to solve problems and perform tasks. Two essential construction materials in the industry are crumb rubber and destroyed aggregates. For accurate Marshall Stability mix proportioning, this work establishes the usage of ANNtechniques. Five of the most widely used statistical metrics are Pearson correlation coefficient, mean absolute error, and root mean square errors. When compared to other applied models, ANN produces better results. Proposed models should save money in terms of materials, labour, and time while also improving accuracy. The recommended concrete should be more cost-effective and long-lasting.The recommended values such as CC= 0.9484, Mean Absolute error=0.7988, RMSE=0.9478 represents that the result should be more cost-effective and long-lasting.