Novel hybrid models to predict the capillary water absorption values of building stones

Abstract The water that moves upward inside the stone is affected by capillary absorption (CWA). This trend in historic and old buildings causes rapid destruction. In simple regression model, relationship between CWA with resistance (compressive strength CS) its physical characteristics, such as (water weight ( ${W}_{a}$?> W a ), surface porosity $n$?> n P-wave velocity ${V}_{p}$?> V p dry unit ${\rho }_{d}$?> ? d )) can be extracted. Several samples were collected from several rocks. To aim prediction design, SVR ANFIS models proposed, which two main variables optimal quantity of SVR’s decisive indicated via linking a multi-verse optimizer (MVO) algorithm. So to develop models, gathered data records for estimating published articles separated into parts after being sorted randomly. Numerous stones containing igneous, metamorphic, travertine Turkey Anatolia use experimental affairs. outputs hybrid predicting building depict both have justifiable capability process, indicating acceptable correlation recorded predicted values ${CWA}.$?> . All all, it proved MVO-SVR has best performance among comprising approaches.