ANFIS-based prediction of the compressive strength of geopolymers with seeded fly ash and rice husk-bark ash

作者：Nazari Ali^*; Khalaj Gholamreza; Riahi Shadi

来源：Neural Computing & Applications, 2013, 22(3-4): 689-701.

DOI：10.1007/s00521-011-0751-y

• Geopolymer
• Compressive strength
• Fly ash
• Rice husk-bark ash
• ANFIS
• FTIR
• Curing regime

In the present work, compressive strength 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 forms and a mixture of water glass and NaOH mixture as alkali activator, were subjected to compressive strength tests at 7 and 28 days of curing. The curing regimes were different: one set of the specimens were cured in water at room temperature until 7 and 28 days and the other sets were oven-cured for 36 h at the range of 40-90A degrees C and then cured at room temperature until 7 and 28 days. A model based on ANFIS for predicting the compressive strength of the specimens has been presented. To build the model, training and testing using experimental results from 120 specimens were conducted. The used data as the inputs of ANFIS models are arranged in a format of six parameters that cover the percentage of fine fly ash in the ashes mixture, the percentage of coarse fly ash in the ashes mixture, the percentage of fine rice husk-bark ash in the ashes mixture, the percentage of coarse rice husk-bark ash in the ashes mixture, the temperature of curing, and the time of water curing. According to these input parameters in the ANFIS models, the compressive strength of each specimen was predicted. The training and testing results in ANFIS models showed a strong potential for predicting the compressive strength of the geopolymeric specimens.

• 出版日期2013-3