Predicting Compressive Strength of Recycled Aggregate Concrete by Multiple Regression Analysis

Abstract:

Today, efforts are underway in a number of areas to conserve the environment and protect natural resource. In the construction industry, many researchers have studied the development of new concrete using recycled aggregate (RA). This research proposes a multiple regression model (MRM) for predicting the compressive strength of recycled aggregate concrete (RAC). The compressive strength data of 85 specimens of RAC strengths were used for constructing and evaluating the prediction model. The average error rate of the constructed MRM evaluation is 7.18 percent. This result will be useful for predicting the compressive strength of RAC using multiple regression analysis.

• Periodical: Applied Mechanics and Materials (Volumes 253-255)
• Pages: 546-549
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.253-255.546
• Online since: December 2012
• Authors: Yoon Seok Shin, Gwang Hee Kim
• Keywords: Multiple Regression Analysis, Predicting Compressive Strength, Recycled Aggregate Concrete (RAC)

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