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The present study is a continuation of a previously published by the authors. In Part I, mechanical data of Alkaline-treated natural fibers-reinforced plaster was examined using response surface methodology (RSM) statistics, while in this work (Part II), the data are analyzed using Artificial neural network (ANN) statistics. Many studies have focused on substituting synthetic fibers by natural fibers in plaster matrix. The present study reports ANN statistics data analysis on the mechanical properties of plaster and natural fibers. ANN and RSM methods are employed and their findings discussed. During this study, flexural properties of sodium hydroxide solution (NaOH)-treated natural fibers in plaster mortars were investigated. Experimental data effects were established by analysis of variance (ANOVA) method. Fiber length optimization and NaOH percentage treatment of fibers were also performed utilizing desirability function DF to obtain maximum flexural properties. Experimental results showed good agreement with those obtained statistically. The ANN and RSM models also have correlated highly to the experimental data. However, the ANN model proves more to be accurate.

journal of natural fibers

The Effect of Alkaline Treatment on Mechanical Performance of Natural Fibers-Reinforced Plaster: Part II Optimization Comparison between ANN and RSM Statistics