Neuro-evolutionary optimization methodology applied to the synthesis process of ash based adsorbents

被引：14

作者：

Curteanu, Silvia ^{[1
]}

Buema, Gabriela ^{[1
]}

Piuleac, Ciprian George ^{[1
]}

Sutiman, Daniel Mircea ^{[1
]}

Harja, Maria ^{[1
]}

机构：

[1] Gheorghe Asachi Tech Univ Iasi, Fac Chem Engn & Environm Protect, Dept Chem Engn, Iasi 700050, Romania

来源：

JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY | 2014年 / 20卷 / 02期

关键词：

Adsorption; Stacked neural network; Genetic algorithm; Optimization; Ash; COAL FLY-ASH; MULTIOBJECTIVE OPTIMIZATION; POWER-PLANTS; ADSORPTION; ZEOLITES; REMOVAL; TEMPERATURE; MEMBRANES; IONS; LEAD;

D O I：

10.1016/j.jiec.2013.05.020

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

Ash and modified ash were investigated as alternative adsorbents for copper ions. Our aim was to establish optimal working conditions for obtaining the new adsorbents, using a neuro-evolutionary optimization methodology. The materials were characterized by SEM, FT-IR, EDAX, XRD, and by the removal percentage. Three multilayer perceptron neural networks were developed and aggregated into a stack to form the model of the process. The neural model was integrated into an optimization procedure solved with a genetic algorithm to obtain the optimum values for the percentage of adsorption. The new adsorbents provide two benefits: environmental protection and energy recovery. (C) 2013 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved.

引用

页码：597 / 604

页数：8

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