Prediction of Compressive Strength Behavior of Ground Bottom Ash Concrete by an Artificial Neural Network

Table 10

Weight matrices and bias vectors of the optimal ANN model.

1st hidden layer					2st hidden layer		Output layer
Weight values				Bias values	Weight values	Bias value	Weight values	Bias value
2.2520432051	−0.3981712674	0.1426346319	−0.0140866410	−3.4309213367	−0.1391796254	1.9325463746	−66.2254046159	63.2786024914
−1.3586053592	−0.0135040464	−0.0106928619	0.0006243239	−0.6791399848	−20.4516033471
−37.8060871011	−0.0142097100	−0.0097865080	−0.1312560306	13.0270855658	−5.2081025307
−1.4842859686	−0.0225482951	0.0129510442	−0.0345802726	2.3163310389	0.2904504482
−1.5862514326	−0.0278216812	−0.0176569269	0.0011291431	−0.5617265081	11.8122578704
−0.3361430039	0.0009375362	0.0017038103	−0.1433868490	−2.9575403959	10.8229621316