Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq

  • Basim Hussein Khudair College of Engineering-University of Baghdad
  • Sura Kareem Ali College of Engineering-University of Baghdad
  • Duaa Tawfeeq Jassim College of Engineering-University of Baghdad

Abstract

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.


 

Published
2018-05-01
How to Cite
KHUDAIR, Basim Hussein; ALI, Sura Kareem; JASSIM, Duaa Tawfeeq. Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq. Journal of Engineering, [S.l.], v. 24, n. 5, p. 113-123, may 2018. ISSN 2520-3339. Available at: <https://jcoeng.edu.iq/index.php/main/article/view/j.eng.2018.05.08>. Date accessed: 24 may 2018. doi: https://doi.org/10.31026/j.eng.2018.05.08.