Application of fuzzy logic approach in predicting the lateral confinement coefficient for RC columns wrapped with CFRP

Degradation of azinphos-methyl and chlorpyrifos from aqueous solutions by ultrasound treatment

“…Moreover, the p-value is used as a useful statistical tool to check the significance of each of the coefficients. The variable with the larger tratio and with the smaller p-value is considered as the more significant parameter in the regression model [24,25] It is also noted that values that yield Prob(t) factors (or p-values) N 0.9 can be omitted until all remaining factors are calculated at once [24][25][26]. In the study, the significance of each coefficient was determined by Student's t-test and pvalues, which are presented in Tables 2 and 3.…”

Implementation of fuzzy logic approach to estimate the degree of expulsion and spattering index and weld strength in projection welding

“…In this study, the present fuzzy set categories were expressed in the form of letters (i.e., A, B, C, etc.) to build simple fuzzy rules, as similarly performed in the previous studies [14,38,40,44]. Therefore, the model variables had two-, eight-, ten-, or fourteen-level trapezoidal-shaped membership functions (trapmfi, where i = 1, 2, 3, …, 14) namely A, B, C, D, E, F, G, H, I, J, K, L, M and N instead of long linguistic terms such as moderately low, low, moderate, moderately high, high, very high, etc.…”

“…In the literature, the variable with the larger t-ratio and with the smaller p value is regarded as the more significant parameter in the regression model [14,15,38,40,41,47,48]. According to the absolute tratios with the smaller p values and standard errors, weld current (I) and electrode force (F e ) showed more synergistic importance than other components for the best-fit regression models in estimation of E and F k for both DC 04 and DP 600 steel sheets (Table 4).…”

“…Although many of classical models may give a good insight into the fundamental principles, they need to be simplified, since the mechanisms ruling a specific system may not be understood and formulated explicitly [13][14][15]. Therefore, artificial intelligence-based computational techniques have recently found a wide application in industrial and commercial control for modeling of various nonlinear system dynamics.…”

Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete

“…More specifically, in the field of concrete structures strengthened with FRP systems there are examples where DM algorithms have been used to predict the lateral confinement coefficient for reinforced concrete columns wrapped with CFRP [12], the strength of FRP confined concrete cylinders [13], the shear strength of reinforced concrete beams reinforced with FRP systems using either the externally bonded (EBR) [14] or the NSM [15] techniques or even the bond strength of FRP EBR systems in concrete [16]. According to the author's best knowledge, only one work of their authorship is available where DM algorithms were applied to predict the bond strength of NSM FRP systems in concrete [17].…”