Prediction Model of Compressive Strength of Fly Ash-Slag Concrete Based on Multiple Adaptive Regression Splines
نویسندگان
چکیده
Accurate prediction of compressive strength concrete is one the key issues in industry. In this paper, a method fly ash-slag based on multiple adaptive regression splines (MARS) proposed, and model analysis process determined by analyzing principle algorithm. Based Concrete Compressive Strength dataset UCI, MARS for was constructed with cement content, blast furnace slag powder ash water reducing agent coarse aggregate fine content age as independent variables. The results artificial neural network (BP), random forest (RF), support vector machine (SVM), extreme learning (ELM), nonlinear (MnLR) were compared analyzed, accuracy stability RF models had obvious advantages, comprehensive performance slightly better than that model. Finally, explicit expression given, which provides an effective to achieve concrete.
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ژورنال
عنوان ژورنال: Open Journal of Applied Sciences
سال: 2022
ISSN: ['2165-3917', '2165-3925']
DOI: https://doi.org/10.4236/ojapps.2022.123021