Prediction of Municipal Solid Waste Generation by Use of Artificial Neural Network: A Case Study of Mashhad
Journal Title: International Journal of Environmental Research - Year 2008, Vol 2, Issue 1
Abstract
Accurate prediction of municipal solid waste’s quality and quantity is crucial for designing and programming municipal solid waste management system. But predicting the amount of generated waste is difficult task because various parameters affect it and its fluctuation is high. In this research with application of feed forward artificial neural network, an appropriate model for predicting the weight of waste generation in Mashhad, was proposed. For this purpose, a time series of Mashhad’s generated waste which have been arranged weekly, from 2004 to 2007, was used. Also, for recognizing the effect of each input data on the waste generation sensitive analysis was performed. Finally, different structures of artificial network were investigated and then the best model for predicting Mashhad’s waste generation was chosen based on mean absolute error (MAE), mean absolute relative error (MARE), root mean square error (RMSE), correlation coefficient (R2) and threshold statistics (TS) indexes. After performing of the mentioned model, correlation coefficient (R2) and mean absolute relative error (MARE) in neural network for test have been achieved equal to 0.746 and 3.18% respectively. Results point that artificial neural network model has more advantages in comparison with traditional methods in predicting the municipal solid waste generation.
Authors and Affiliations
M. Jalili Ghazi Zade, R. Noori
Keywords
Related Articles
- EP ID EP82710
- DOI -
- Views 136
- Downloads 0
Removal of Mercury from Aqueous Solutions by Waste Brick
Mercury is one of the most toxic heavy metals present in aquatic systems, exhibiting a complex behaviour in the environment, where it may persist for decades after the source of pollution is stopped. Hence, it is importa...
Determination of Toxic Toluene, Xylene and Cumene in Different Lake Waters
A rapid and reproducible method is described that employs solid phase extraction (SPE) using dichloromethane, followed by gas chromatograph-mass spectrometry for the determination of toxic toluene, xylene and cumene (TXC...
Evaluating the Recovery Potential of Solid Wastes
The purpose of this research was to evaluate the recovery potential of solid waste in Mashhad. The solid waste generated in the regions 4, 5 and 6 has been quantified and characterized using direct weighing, physical tes...
Rural Solid Waste Management<br />
The province of Bushehr is located in southern area of Iran and north of Persian Gulf. Solid waste management in Bushehr’s villages was the aim of this research. For the sake of this study, 21 villages scattered all over...
Prediction of MSW Long-term Settlement Induced by Mechanical and Decomposition-Based Compressions
Long-term settlement of MSW landfills is a complex process, which is explained by the following two mechanisms: (1) the mechanical long-term compression of degradable organic solids (DOS) and un-degradable organic solids...