1st International Future Engineering Conference, Şırnak, Türkiye, 25 - 26 Aralık 2023, ss.24-30
With a primary focus on leveraging time-series analysis and data mining methodologies, this paper delves
into the realm of geopolymer mortars, an eco-friendly and energy-efficient construction material. The target
of the study is to specify the variables that affect the compressive strength of geopolymer mortars and then
utilize those variables to estimate the mechanical property (compressive strength (CS)) of mortars in the
future. The study analyzed the effects of factors such as compressive strength, obsidian, glass waste, fly ash,
and heat on the CS of mortar. ARIMA model is adeptly employed to forecast the short-term compressive
strength of geopolymers endowed with five distinct properties and subjected to varying temperatures. A 30-
day compressive strength prediction was made based on the 28 day compressive strengths. As a result of the
analysis, the highest RMSE, MAE, MAPE and R2 values were obtained as 1.207, 0.983, 0.025 and 0.941,
respectively. Those results emphasize how well-sophisticated statistical modelling approaches could be
employed to understand and estimate the dynamics of compressive strength in geopolymer mortars.