Development of artificial neural network model for the analysis of wastewater treatment
A statistical modeling tool called artificial neural network (ANN) is used in this work to predict the performance of wastewater treatment plant (WWTP). Extensive influent and effluent parameters database containing measured data spanning over two years of period was used to develop and train ANN u...
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| Format: | Monograph |
| Language: | English |
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s.n
2012
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| Online Access: | http://irep.iium.edu.my/35513/1/EDW_B0805-151_RR.pdf |
| _version_ | 1825647883240603648 |
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| author | Jami, Mohammed Saedi |
| author_facet | Jami, Mohammed Saedi |
| author_sort | Jami, Mohammed Saedi |
| collection | IIUM |
| description | A statistical modeling tool called artificial neural network (ANN) is used in this work to predict the performance of wastewater treatment plant (WWTP).
Extensive influent and effluent parameters database containing measured data spanning over two years of period was used to develop and train ANN using ANN toolbox in commercially available software, MATLAB. The data were obtained from one of Sewage Treatment Plant in Malaysia. The input parameters for the ANN were BOD,SS, and COD of the influent, while the output parameters were combination of the effluent characteristics. The networks for single input-single output were compared with those of single input-multiple output. |
| first_indexed | 2024-03-05T23:24:09Z |
| format | Monograph |
| id | oai:generic.eprints.org:35513 |
| institution | International Islamic University Malaysia |
| language | English |
| last_indexed | 2024-03-05T23:24:09Z |
| publishDate | 2012 |
| publisher | s.n |
| record_format | dspace |
| spelling | oai:generic.eprints.org:355132014-03-10T08:58:54Z http://irep.iium.edu.my/35513/ Development of artificial neural network model for the analysis of wastewater treatment Jami, Mohammed Saedi T Technology (General) A statistical modeling tool called artificial neural network (ANN) is used in this work to predict the performance of wastewater treatment plant (WWTP). Extensive influent and effluent parameters database containing measured data spanning over two years of period was used to develop and train ANN using ANN toolbox in commercially available software, MATLAB. The data were obtained from one of Sewage Treatment Plant in Malaysia. The input parameters for the ANN were BOD,SS, and COD of the influent, while the output parameters were combination of the effluent characteristics. The networks for single input-single output were compared with those of single input-multiple output. s.n 2012-03-14 Monograph NonPeerReviewed application/pdf en http://irep.iium.edu.my/35513/1/EDW_B0805-151_RR.pdf Jami, Mohammed Saedi (2012) Development of artificial neural network model for the analysis of wastewater treatment. Research Report. s.n, Kuala Lumpur. (Unpublished) EDW B0805-151 |
| spellingShingle | T Technology (General) Jami, Mohammed Saedi Development of artificial neural network model for the analysis of wastewater treatment |
| title | Development of artificial neural network model for the analysis of wastewater treatment |
| title_full | Development of artificial neural network model for the analysis of wastewater treatment |
| title_fullStr | Development of artificial neural network model for the analysis of wastewater treatment |
| title_full_unstemmed | Development of artificial neural network model for the analysis of wastewater treatment |
| title_short | Development of artificial neural network model for the analysis of wastewater treatment |
| title_sort | development of artificial neural network model for the analysis of wastewater treatment |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/35513/1/EDW_B0805-151_RR.pdf |
| work_keys_str_mv | AT jamimohammedsaedi developmentofartificialneuralnetworkmodelfortheanalysisofwastewatertreatment |