A Statistical Approach to Predicting Fresh State Properties of Sustainable Concrete
暂无分享,去创建一个
[1] Jerry Stephens,et al. Performance of 100% Fly Ash Concrete with 100% Recycled Glass Aggregate , 2011 .
[2] Mukesh Limbachiya,et al. Performance of portland/silica fume cement concrete produced with recycled concrete aggregate , 2012 .
[3] Umit Atici,et al. Prediction of the strength of mineral admixture concrete using multivariable regression analysis and an artificial neural network , 2011, Expert Syst. Appl..
[4] Qian Chen,et al. Comparison of Data Mining Techniques for Predicting Compressive Strength of Environmentally Friendly Concrete , 2016, J. Comput. Civ. Eng..
[5] Ruoyu Jin,et al. Survey of the current status of sustainable concrete production in the U.S. , 2015 .
[6] M. A. Bhatti,et al. Predicting the compressive strength and slump of high strength concrete using neural network , 2006 .
[7] Vinay Agrawal,et al. Prediction of Slump in Concrete using Artificial Neural Networks , 2010 .
[8] Aditya Kumar,et al. Machine learning to predict properties of fresh and hardened alkali-activated concrete , 2021 .
[9] P. Livesey,et al. Strength characteristics of Portland-limestone cements , 1991 .