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This study is based on the usage of a composite of zinc sulfide nanoparticles with activated carbon (ZnS-NPs-AC) for the adsorption of methylene blue (MB) from aqueous solutions. The properties of ZnS-NPs-AC were identified by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS) and Fourier transformation infrared spectroscopy (FTIR). Response surface methodology (RSM), an artificial neural network (ANN) and the least squares-support vector machine (LS-SVM) were used for the optimization and/or modeling of pH, ZnS-NPs-AC mass, MB concentration and sonication time to develop respective predictive equations for the simulation of the efficiency of MB adsorption. The obtained results using LS-SVM and ANN exhibit two nonlinear approaches (LS-SVM and ANN models) which show better performances in comparison to central …