Prediction total specific pore volume of geopolymers produced from waste ashes by ANFIS

In the present work, total specific pore volume of geopolymers which made from a mixture of fly ash and rice husk bark ash has been predicted by adaptive network-based fuzzy inference systems (ANFIS). Different specimens were subjected to porosimetry tests at 7 and 28 days of curing. One set of the specimens were water cured at room temperature until reaching to 7 and 28 days and the other sets were oven cured for 36 h at the range of 40–90 °C and then water cured at room temperature until 7 and 28 days. To build the model, training and testing were conducted by using experimental results from 120 specimens. According to the input parameters in the ANFIS models, the pore volume of each specimen was predicted. The training and testing results in the ANFIS models showed a strong potential for predicting the total specific pore volume of the geopolymeric specimens in the considered range.