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Application of least squares support vector regression and linear multiple regression for modeling removal of methyl orange onto tin oxide nanoparticles loaded on activated carbon and activated carbon prepared from Pistacia atlantica wood
Journal article   Peer reviewed

Application of least squares support vector regression and linear multiple regression for modeling removal of methyl orange onto tin oxide nanoparticles loaded on activated carbon and activated carbon prepared from Pistacia atlantica wood

M. Ghaedi, Mahmoud reza Rahimi, A.M. Ghaedi, Inderjeet Tyagi, Shilpi Agarwal and Vinod Kumar Gupta
Journal of colloid and interface science, Vol.461, pp.425-434
01/01/2016
PMID: 26414425

Abstract

Isotherm Least square support vector Methyl orange Nanoparticles Tin oxide

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