DocumentCode :
1873344
Title :
AI-based prediction and diagnostic on bioethanol production
Author :
Vassileva, Svetla ; Doukovska, Lyubka ; Mileva, Silvia
Author_Institution :
Dept. of Integrated Syst., ISER, Sofia, Bulgaria
fYear :
2012
fDate :
6-8 Sept. 2012
Firstpage :
270
Lastpage :
274
Abstract :
Nowadays biomass is used to meet a variety of energy needs, including generating electricity, heating homes, fueling vehicles and providing process heat for industrial facilities. Bioethanol is ethanol (C2H5OH) produced by the biological fermentation of carbohydrates derived from plant material and from the food industry. In terms of fuel use, ethanol is mainly of interest as a petrol additive or substitute. This paper presents a detailed study on ethanol fermentation, carried out by yeasts, based on full experimental plan and artificial intelligence prediction methods application. Presented results are applicable to industrial applications for biofuels production and related technological process functional diagnostic systems.
Keywords :
additives; artificial intelligence; biofuel; biotechnology; fermentation; microorganisms; organic compounds; petroleum; process heating; production engineering computing; renewable materials; AI-based diagnostic; AI-based prediction; artificial intelligence prediction method application; bioethanol production; biofuel production; biological fermentation; biomass; carbohydrates; electricity generation; ethanol fermentation; ethanol production; food industry; heating; industrial facilities; petrol additive; petrol substitute; plant material; process heat; technological process functional diagnostic systems; vehicle fueling; yeasts; Adaptation models; Artificial neural networks; Biological system modeling; Biomass; Ethanol; Mathematical model; Predictive models; artificial intelligence; bioethanol; biofuels; diagnostics; prediction; yeast fermentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems (IS), 2012 6th IEEE International Conference
Conference_Location :
Sofia
Print_ISBN :
978-1-4673-2276-8
Type :
conf
DOI :
10.1109/IS.2012.6335147
Filename :
6335147
Link To Document :
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