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• W3000434541 startingPage "122781" @default.
• W3000434541 abstract "To establish the models of microbial lipid production from cellulosic ethanol wastewater by R. glutinis, the biomass, lipid yield, and COD removal rate were investigated under different conditions. Subsequently, the genetic algorithm based on SVM was adopted to optimize parameters for obtaining the maximum biomass. The results demonstrated that the initial COD and glucose content had a significant effect on lipids synthesis. Most of the organic matter in the wastewater was consumed with the production of lipid. Compared with BP-ANN, SVM had better fitting and generalization ability for small amount of experimental data. By genetic algorithm optimization based on SVM, the maximum biomass and lipid yield could reach 11.87 g/L and 2.18 g/L, respectively. The results suggest that the SVM model could be used as an effective tool to optimize fermentation conditions." @default.
• W3000434541 created "2020-01-23" @default.
• W3000434541 creator A5014360756 @default.
• W3000434541 creator A5015500789 @default.
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• W3000434541 date "2020-04-01" @default.
• W3000434541 modified "2023-10-16" @default.
• W3000434541 title "Modeling and optimization of microbial lipid fermentation from cellulosic ethanol wastewater by Rhodotorula glutinis based on the support vector machine" @default.
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• W3000434541 doi "https://doi.org/10.1016/j.biortech.2020.122781" @default.
• W3000434541 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31954963" @default.
• W3000434541 hasPublicationYear "2020" @default.
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