Artificial Neural Network and Full Factorial Design Assisted AT-MRAM on Fe Oxides, Organic Materials, and Fe/Mn Oxides in Surficial Sediments

作     者：GAO Qian WANG Zhi-zeng WANG Qian LI Shan-shan LI Yu 

作者机构：Research Academy of Energy and Environmental Studies North China Electric Power University Beijing 102206 P. R. China 

基　　金：Supported by the National Natural Science Foundation of China(No.50879025) 

出 版 物：《Chemical Research in Chinese Universities》 (高等学校化学研究（英文版）)

年 卷 期：2011年第27卷第6期

页      码：944-948页

摘      要：Artificial neural network（ANN） and full factorial design assisted atrazine（AT） multiple regression adsorption model（AT-MRAM） were developed to analyze the adsorption capability of the main components in the surficial sediments（SSs）. Artificial neural network was used to build a model（the determination coefficient square r2 is 0.9977） to describe the process of atrazine adsorption onto SSs, and then to predict responses of the full factorial design. Based on the results of the full factorial design, the interactions of the main components in SSs on AT adsorption were investigated through the analysis of variance（ANOVA）, F-test and t-test. The adsorption capability of the main components in SSs for AT was calculated via a multiple regression adsorption model（MRAM）. The results show that the greatest contribution to the adsorption of AT on a molar basis was attributed to Fe/Mn（–1.993 μmol/mol）. Organic materials（OMs） and Fe oxides in SSs are the important adsorption sites for AT, and the adsorption capabilities are 1.944 and 0.418 μmol/mol, respectively. The interaction among the non-residual components（Fe, Mn oxides and OMs） in SSs interferes in the adsorption of AT that shouldn’t be neglected, revealing the significant contribution of the interaction among non-residual components to controlling the behavior of AT in aquatic environments.

主 题 词：Back propagation(BP) artificial neural network Full factorial design Fe/Mn oxide Organic material Atrazine Interaction 

学科分类：12[管理学] 02[经济学] 07[理学] 08[工学] 070103[070103] 0202[经济学-财政学类] 020208[020208] 1201[管理学-管理科学与工程类] 081104[081104] 0714[0714] 0835[0835] 0701[理学-数学类] 0811[工学-水利类] 0812[工学-测绘类] 

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