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Back Propagation Neural Network Model for Predicting the Performance of Immobilized Cell Biofilters Handling Gas-Phase Hydrogen Sulphide and Ammonia
Joint Authors
López, M. Estefanía
Kim, Jung Hoon
Park, Hung Suck
Rene, Eldon R.
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-07
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Lab scale studies were conducted to evaluate the performance of two simultaneously operated immobilized cell biofilters (ICBs) for removing hydrogen sulphide (H2S) and ammonia (NH3) from gas phase.
The removal efficiencies (REs) of the biofilter treating H2S varied from 50 to 100% at inlet loading rates (ILRs) varying up to 13 g H2S/m3·h, while the NH3 biofilter showed REs ranging from 60 to 100% at ILRs varying between 0.5 and 5.5 g NH3/m3·h.
An application of the back propagation neural network (BPNN) to predict the performance parameter, namely, RE (%) using this experimental data is presented in this paper.
The input parameters to the network were unit flow (per min) and inlet concentrations (ppmv), respectively.
The accuracy of BPNN-based model predictions were evaluated by providing the trained network topology with a test dataset and also by calculating the regression coefficient (R2) values.
The results from this predictive modeling work showed that BPNNs were able to predict the RE of both the ICBs efficiently.
American Psychological Association (APA)
Rene, Eldon R.& López, M. Estefanía& Kim, Jung Hoon& Park, Hung Suck. 2013. Back Propagation Neural Network Model for Predicting the Performance of Immobilized Cell Biofilters Handling Gas-Phase Hydrogen Sulphide and Ammonia. BioMed Research International،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1030568
Modern Language Association (MLA)
Rene, Eldon R.…[et al.]. Back Propagation Neural Network Model for Predicting the Performance of Immobilized Cell Biofilters Handling Gas-Phase Hydrogen Sulphide and Ammonia. BioMed Research International No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-1030568
American Medical Association (AMA)
Rene, Eldon R.& López, M. Estefanía& Kim, Jung Hoon& Park, Hung Suck. Back Propagation Neural Network Model for Predicting the Performance of Immobilized Cell Biofilters Handling Gas-Phase Hydrogen Sulphide and Ammonia. BioMed Research International. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1030568
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1030568