Introducing an evolutionary-decomposition model for prediction of municipal solid waste flow: application of intrinsic time-scale decomposition algorithm

Owing to the importance of municipal waste as a determining factor in waste management, developing data-driven models in waste generation data is essential. In the current study, solid waste generation is taken as the function of several parameters, namely month, rainfall, maximum temperature, avera...

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Bibliographic Details
Published in:	Engineering applications of computational fluid mechanics Vol. 15; no. 1; pp. 1159 - 1175
Main Authors:	Fan, Linyuan, Abbasi, Maryam, Salehi, Kazhal, Band, Shahab S., Chau, Kwok-Wing, Mosavi, Amir
Format:	Journal Article
Language:	English
Published:	Hong Kong Taylor & Francis 01.01.2021 Taylor & Francis Ltd Taylor & Francis Group
Subjects:	Algorithms artificial intelligence circular economy (CE) Coefficients Decomposition Empirical equations Forecasting Gene expression gene expression programming intrinsic time-scale decomposition (ITD) algorithm Machine learning Mathematical models Mean square errors Monte Carlo simulation Municipal solid waste Municipal waste management Optimization Parameters Programming Rainfall Reliability Resampling Root-mean-square errors Solid waste management Solid wastes Training Waste management
ISSN:	1994-2060, 1997-003X
Online Access:	Get full text
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