Comparative Study of Artificial Neural Network and Response Surface Methodology for Modelling and Optimization the Adsorption Capacity of Fluoride onto Apatitic Tricalcium Phosphate
作者： A. El Rhilassi , A. Taitai , M.Bennani-Ziatni , M.Mourabet
DOI: 10.13189/UJAM.2014.020202
关键词:
摘要: In this study, Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were employed to develop an approach for the evaluation of fluoride adsorption process. A batch process was performed using apatitic tricalcium phosphate adsorbent, remove ions from aqueous solutions. The effects variables which are pH, adsorbent mass, initial concentration, temperature, on capacity ( ����ℯ (mg/g)) investigated through three-levels, four-factors Box-Behnken (BBD) designs. Same design also utilized obtain a training set ANN. results two methodologies compared their predictive capabilities in terms coefficient
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