Experimental investigations and ANFIS prediction of water absorption of geopolymers produced by waste ashes

In the present work, percentage of water absorption of geopolymers made from seeded fly ash and rice husk bark ash has been predicted by adaptive network-based fuzzy inference systems (ANFIS). Different specimens, made from a mixture of fly ash and rice husk bark ash in fine and coarse, water glass and NaOH solution, were subjected to permeability tests at 7 and 28 days of curing. The curing regime was different: one set 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 cured at room temperature until 7 and 28 days. A model based on ANFIS for predicting the percentage of water absorption of the specimens has been presented. To build the model, training and testing using experimental results from 120 specimens were conducted. According to these input parameters, in the ANFIS models, the percentage of water absorption of each specimen was predicted. The training and testing results in the ANFIS models have shown a strong potential for predicting the percentage of water absorption of the geopolymer specimens.