Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq
The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities...
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| Format: | Article |
| Language: | English |
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University of Baghdad
2018-05-01
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| Series: | Journal of Engineering |
| Subjects: | |
| Online Access: | http://joe.uobaghdad.edu.iq/index.php/main/article/view/588 |
| _version_ | 1797718964757856256 |
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| author | Basim Hussein Khudair Sura Kareem Ali Duaa Tawfeeq Jassim |
| author_facet | Basim Hussein Khudair Sura Kareem Ali Duaa Tawfeeq Jassim |
| author_sort | Basim Hussein Khudair |
| collection | DOAJ |
| description | The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. The artificial neural networks show a high coefficient of determination between the predicted and observed domestic solid waste, with R2 value reaching to 0.91, 0.828 and 0.827 for Al-Karkh, 0.9986,0. 9903 and 0.9903 for Rusafa side, and 0.9989, 0.9878 and 0.9847 in Baghdad city, and also, these models were used to estimate the generation of municipal solid waste for short period with highly efficient which assistance in planning to design landfills sites. |
| first_indexed | 2024-03-12T08:57:53Z |
| format | Article |
| id | doaj.art-8986e64676f8472f9a2a8f1c7d7842d9 |
| institution | Directory Open Access Journal |
| issn | 1726-4073 2520-3339 |
| language | English |
| last_indexed | 2024-03-12T08:57:53Z |
| publishDate | 2018-05-01 |
| publisher | University of Baghdad |
| record_format | Article |
| series | Journal of Engineering |
| spelling | doaj.art-8986e64676f8472f9a2a8f1c7d7842d92023-09-02T15:52:15ZengUniversity of BaghdadJournal of Engineering1726-40732520-33392018-05-0124510.31026/j.eng.2018.05.08Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, IraqBasim Hussein Khudair0Sura Kareem Ali1Duaa Tawfeeq Jassim2College of Engineering-University of BaghdadCollege of Engineering-University of BaghdadCollege of Engineering-University of BaghdadThe importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. The artificial neural networks show a high coefficient of determination between the predicted and observed domestic solid waste, with R2 value reaching to 0.91, 0.828 and 0.827 for Al-Karkh, 0.9986,0. 9903 and 0.9903 for Rusafa side, and 0.9989, 0.9878 and 0.9847 in Baghdad city, and also, these models were used to estimate the generation of municipal solid waste for short period with highly efficient which assistance in planning to design landfills sites.http://joe.uobaghdad.edu.iq/index.php/main/article/view/588Baghdad municipalities, Karkh, Rusafa, municipal solid waste, ANN |
| spellingShingle | Basim Hussein Khudair Sura Kareem Ali Duaa Tawfeeq Jassim Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq Journal of Engineering Baghdad municipalities, Karkh, Rusafa, municipal solid waste, ANN |
| title | Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq |
| title_full | Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq |
| title_fullStr | Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq |
| title_full_unstemmed | Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq |
| title_short | Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq |
| title_sort | prediction of municipal solid waste generation models using artificial neural network in baghdad city iraq |
| topic | Baghdad municipalities, Karkh, Rusafa, municipal solid waste, ANN |
| url | http://joe.uobaghdad.edu.iq/index.php/main/article/view/588 |
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