title: Prediction of the compression ratio for municipal solid waste using decision tree.
abstract: The compression ratio of municipal solid waste (MSW) is an essential parameter for evaluation of waste settlement and landfill design. However, no appropriate model has been proposed to estimate the waste compression ratio so far. In this study, a decision tree method was utilized to predict the waste compression ratio (C'c). The tree was constructed using Quinlan's M5 algorithm. A reliable database retrieved from the literature was used to develop a practical model that relates C'c to waste composition and properties, including dry density, dry weight water content, and percentage of biodegradable organic waste using the decision tree method. The performance of the developed model was examined in terms of different statistical criteria, including correlation coefficient, root mean squared error, mean absolute error and mean bias error, recommended by researchers. The obtained results demonstrate that the suggested model is able to evaluate the compression ratio of MSW effectively.
authors.affiliation: School of Civil Engineering, Iran University of Science and Technology (IUST), Tehran, Iran.
authors.forename: Ali Akbar
authors.initials: AA
authors.lastname: Heshmati R
authors.forename: Maryam
authors.initials: M
authors.lastname: Mokhtari
authors.forename: Saeed
authors.initials: S
authors.lastname: Shakiba Rad
mesh_terms: D000465:Algorithms; D003663:Decision Trees; D012037:Refuse Disposal / Q000379:methods*; D062611:Solid Waste; D014867:Water
chemical_list: D062611:Solid Waste; D014867:Water
keywords: M5 algorithm; Municipal solid waste; compression ratio; decision tree; statistical criteria; waste settlement