Prediction of Concrete Properties Using Multiple Linear Regression and Artificial Neural Network
作者： N. Charhate , S. , Subhedar , M. , Adsul
DOI: 10.22115/SCCE.2018.112140.1041
关键词:
摘要: The selection of appropriate type and grade concrete for a particular application is the critical step in any construction project. Workability compressive strength are two significant parameters that need special attention. This study aims to predict slump along with 7-days & 28-days based on data collected from various RMC plants. There many studies reported general address this issue time over long period. However, considering worldwide use huge quantity infrastructure projects, there scope leads most accurate estimate. Here, mixing plants ongoing sites was M20, M25, M30, M35, M40, M45, M50, M55, M60 M70 concrete. Multiple Linear Regression (MLR) Artificial Neural Network (ANN) models were built as well strength. A variety experiments carried out suggests ANN performs better yields more prediction compared MLR model both
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