Optimization of process parameters for anaerobic fermentation of corn stalk based on least squares support vector machine

被引：50

作者：

Dong, Cuiying ^{[1
,2
]}

Chen, Juan ^{[1
]}

机构：

[1] Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China

[2] Tangshan Univ, Intelligence & Informat Engn Coll, Tangshan 063000, Peoples R China

来源：

BIORESOURCE TECHNOLOGY | 2019年 / 271卷

基金：

中国国家自然科学基金;

关键词：

Pretreatment of corn stalk; LS-SVM; Prediction model; Parameter optimization; BIOGAS PRODUCTION; RICE STRAW; PRETREATMENT; ANN; EXTRACTION; DESIGN; RSM;

D O I：

10.1016/j.biortech.2018.09.085

中图分类号：

S2 [农业工程];

学科分类号：

0828 ;

摘要：

In order to improve the yield and efficiency of biogas produced from anaerobic fermentation of corn stalk, least squares support vector machine (LS-SVM) was used to optimize the pretreatment process parameters. Weight of corn stalk, ultrasonic duration time, alkali pretreatment (2% NaOH) time, and single/dual-frequency ultrasound were selected as the experimental factors of orthogonal experimental design (OED). A new modeling method combining LS-SVM and OED was proposed to establish the predictive model between cumulative biogas production (CBP) and pretreatment process parameters. The effect of experimental factors on CBP was analyzed by two-dimensional (2D) and three-dimensional (3D) contour maps of the predictive model. The optimum parameters for process pretreatment were as follows: weight of corn stalk 53 g, dual-frequency ultrasound, ultrasonic duration time 33 min, alkali pretreatment time 56 h. The CBP of the optimal conditions obtained was 22.69 L and was 14.13% higher than that of optimal conditions for OED.

引用

页码：174 / 181

页数：8

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