Artificial neural network application to the compressive strength of palm kernel shell concrete
نویسندگان
چکیده
منابع مشابه
EVALUATION OF CONCRETE COMPRESSIVE STRENGTH USING ARTIFICIAL NEURAL NETWORK AND MULTIPLE LINEAR REGRESSION MODELS
In the present study, two different data-driven models, artificial neural network (ANN) and multiple linear regression (MLR) models, have been developed to predict the 28 days compressive strength of concrete. Seven different parameters namely 3/4 mm sand, 3/8 mm sand, cement content, gravel, maximums size of aggregate, fineness modulus, and water-cement ratio were considered as input variables...
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This research work focuses on development of Artificial Neural Networks (ANNs) in prediction of compressive strength of concrete after 28 days. To predict the compressive strength of concrete six input parameters that are cement, water, silica fume, super plasticizer, fine aggregate and coarse aggregate are identified. A total of 639 different data sets of concrete was collected from the techni...
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This research deals with the development and comparison of two data-driven models, i.e., Artificial Neural Network (ANN) and Adaptive Neuro-based Fuzzy Inference System (ANFIS) models for estimation of 28-day compressive strength of concrete for 160 different mix designs. These various mix designs are constructed based on seven different parameters, i.e., 3/4 mm sand, 3/8 mm sand, cement conten...
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ژورنال
عنوان ژورنال: MOJ Civil Engineering
سال: 2020
ISSN: 2572-8520
DOI: 10.15406/mojce.2020.06.00164