Prediction of COD and NH4+-N Concentrations in Leachate from Lab-scale Landfill Bioreactors Using Artificial Neural Networks
In this study, we present an Artificial Neural Network (ANN) model for predicting COD and NH4+-N concentrations in landfill leachate from lab-scale landfill bioreactors. For this purpose, two different lab-scale systems were modeled. for neural network’s data obtained. In the first system, the leach...
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| Format: | Article |
| Language: | English |
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Water and Wastewater Consulting Engineers Research Development
2010-06-01
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| Series: | آب و فاضلاب |
| Subjects: | |
| Online Access: | http://www.wwjournal.ir/article_1601_9c6d6f0ef1b82fab996280dca93ffb80.pdf |
| _version_ | 1819157700693458944 |
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| author | Mohamad Javad Zoqi Taktom Zoqi Mohsen Saeedi |
| author_facet | Mohamad Javad Zoqi Taktom Zoqi Mohsen Saeedi |
| author_sort | Mohamad Javad Zoqi |
| collection | DOAJ |
| description | In this study, we present an Artificial Neural Network (ANN) model for predicting COD and NH4+-N concentrations in landfill leachate from lab-scale landfill bioreactors. For this purpose, two different lab-scale systems were modeled. for neural network’s data obtained. In the first system, the leachate from a fresh-waste reactor was drained to a recirculation tank and recycled every two days. In the second, the leachate from a fresh waste landfill reactor was fed through a well-decomposed refuse landfill reactor, while the leachate from a well-decomposed refuse landfill reactor was simultaneously recycled to a fresh waste landfill reactor. The results indicate that leachate NH4+-N and COD concentrations accumulated to a high level in the first system, while. NH4+-N and COD removals were successfully carried out in the second. Also, average removal efficiencies in the second system reached 85% and 34% for COD and NH4+-N, respectively. Finally, the ANN’s results exhibited the success of the model as witnessed by the excellent agreement obtained between measured and predicted values. |
| first_indexed | 2024-12-22T16:12:56Z |
| format | Article |
| id | doaj.art-43d339b1e8184f94a792a4ce1b8f04b8 |
| institution | Directory Open Access Journal |
| issn | 1024-5936 2383-0905 |
| language | English |
| last_indexed | 2024-12-22T16:12:56Z |
| publishDate | 2010-06-01 |
| publisher | Water and Wastewater Consulting Engineers Research Development |
| record_format | Article |
| series | آب و فاضلاب |
| spelling | doaj.art-43d339b1e8184f94a792a4ce1b8f04b82022-12-21T18:20:26ZengWater and Wastewater Consulting Engineers Research Developmentآب و فاضلاب1024-59362383-09052010-06-0121252601601Prediction of COD and NH4+-N Concentrations in Leachate from Lab-scale Landfill Bioreactors Using Artificial Neural NetworksMohamad Javad Zoqi0Taktom Zoqi1Mohsen Saeedi2M.Sc. of Environmental Eng., Faculty Member of Environmental Research Institute of Jahad Daneshgahi, RashtM.Sc. of Artificial Intelligence, Dept. of Computer Engineering, Shiraz UniversityAssoc. Prof., Dept. of Hydraulic and Environmental Eng., School of Civil Eng., Iran Uni. of Science and Tech., TehranIn this study, we present an Artificial Neural Network (ANN) model for predicting COD and NH4+-N concentrations in landfill leachate from lab-scale landfill bioreactors. For this purpose, two different lab-scale systems were modeled. for neural network’s data obtained. In the first system, the leachate from a fresh-waste reactor was drained to a recirculation tank and recycled every two days. In the second, the leachate from a fresh waste landfill reactor was fed through a well-decomposed refuse landfill reactor, while the leachate from a well-decomposed refuse landfill reactor was simultaneously recycled to a fresh waste landfill reactor. The results indicate that leachate NH4+-N and COD concentrations accumulated to a high level in the first system, while. NH4+-N and COD removals were successfully carried out in the second. Also, average removal efficiencies in the second system reached 85% and 34% for COD and NH4+-N, respectively. Finally, the ANN’s results exhibited the success of the model as witnessed by the excellent agreement obtained between measured and predicted values.http://www.wwjournal.ir/article_1601_9c6d6f0ef1b82fab996280dca93ffb80.pdfAnaerobic Processartificial neural networkOrganic ContentNH4+-NLeachate |
| spellingShingle | Mohamad Javad Zoqi Taktom Zoqi Mohsen Saeedi Prediction of COD and NH4+-N Concentrations in Leachate from Lab-scale Landfill Bioreactors Using Artificial Neural Networks آب و فاضلاب Anaerobic Process artificial neural network Organic Content NH4+-N Leachate |
| title | Prediction of COD and NH4+-N Concentrations in Leachate from Lab-scale Landfill Bioreactors Using Artificial Neural Networks |
| title_full | Prediction of COD and NH4+-N Concentrations in Leachate from Lab-scale Landfill Bioreactors Using Artificial Neural Networks |
| title_fullStr | Prediction of COD and NH4+-N Concentrations in Leachate from Lab-scale Landfill Bioreactors Using Artificial Neural Networks |
| title_full_unstemmed | Prediction of COD and NH4+-N Concentrations in Leachate from Lab-scale Landfill Bioreactors Using Artificial Neural Networks |
| title_short | Prediction of COD and NH4+-N Concentrations in Leachate from Lab-scale Landfill Bioreactors Using Artificial Neural Networks |
| title_sort | prediction of cod and nh4 n concentrations in leachate from lab scale landfill bioreactors using artificial neural networks |
| topic | Anaerobic Process artificial neural network Organic Content NH4+-N Leachate |
| url | http://www.wwjournal.ir/article_1601_9c6d6f0ef1b82fab996280dca93ffb80.pdf |
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