Prediction of biochar yield from cattle manure pyrolysis via least squares support vector machine intelligent approach

被引:144
作者
Cao, Hongliang [1 ]
Xin, Ya [1 ]
Yuan, Qiaoxia [1 ]
机构
[1] Huazhong Agr Univ, Coll Engn, Wuhan 430070, Peoples R China
关键词
Cattle manures; Pyrolysis; Biochar yield; Support vector machine; Intelligent modeling; GREENHOUSE-GAS EMISSIONS; MUNICIPAL SOLID-WASTE; BIOMASS GASIFICATION; NEURAL-NETWORK; DAIRY-MANURE; LAND APPLICATION; NITROUS-OXIDE; BED GASIFIERS; CLASSIFIERS; ACTIVATION;
D O I
10.1016/j.biortech.2015.12.024
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
To predict conveniently the biochar yield from cattle manure pyrolysis, intelligent modeling approach was introduced in this research. A traditional artificial neural networks (ANN) model and a novel least squares support vector machine (LS-SVM) model were developed. For the identification and prediction evaluation of the models, a data set with 33 experimental data was used, which were obtained using a laboratory-scale fixed bed reaction system. The results demonstrated that the intelligent modeling approach is greatly convenient and effective for the prediction of the biochar yield. In particular, the novel LS-SVM model has a more satisfying predicting performance and its robustness is better than the traditional ANN model. The introduction and application of the LS-SVM modeling method gives a successful example, which is a good reference for the modeling study of cattle manure pyrolysis process, even other similar processes. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:158 / 164
页数:7
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