Predicting the compressive strength and slump of high strength concrete using neural network

Prediction of punching shear strength of two-way slabs

“…A neural network approach was used to develop a methodology for a concrete mix which has lower cement and water contents, higher durability, better economical and ecological effects [13]. Öztaş et al [14] used a neural network approach to predict the concrete's compressive strength and the slump value. Choi et al [15] proposed an alternative approach for predicting the punching shear strength of concentrically loaded interior slab-column connections using fuzzy logic.…”

Stochastic Modeling of Compressive Strength of Phosphorus Slag Content Cement

“…Exploring the concrete and mortar behavior is an interesting area for researchers resulting in many attentions to prediction of compressive strength via modeling [25]. Common modeling approaches for the prediction of strength properties were generally used including analytical modeling [18,26,27] artificial neural network [28,[29][30][31][32][33][34][35][36][37], and statistical methods [38][39][40][41]. A common classification for the different formulas available for the prediction of compressive strength includes [24]: 1) cement composition-based formulas, 2) constituent-based formulas, 3) maturity concept-based formulas, and 4) strength formulas based on age and the other characteristics.…”

Mining Rules for Satellite Imagery Using Evolutionary Classification Tree

“…There were also much literature [4][5][6][7] proposed complex nonlinear models with highly accuracy for predicting material behavior. But these "black box" models are unable to generate explicit formulas or rules which can explain the essence of the models.…”