Predicting Waste Generation Rate in Tabriz Using Artificial Intelligence (ANN and SVM) Methods and Wavelet Preprocessing for a Long Time

Author

Faculty of Civil Engineering, University of Tabriz, Tabriz , Iran

Abstract

Numerous parameters affect the solid waste production rate, including weather-climate parameters and parameters related to people's economical-social and cultural conditions, format, and detail of the city population, lifestyle, etc. In studying the effects of the mentioned criteria on the waste production rate, classic methods cannot analyze the time-based changes in parameters and the dynamic changes in solid waste production rate. On the other hand, the lack of precise data, an overall plan on solid waste management increases the need for a dynamic method. Linear regression is not a decent method in this research because of the seldom linear relation between parameters. A method, including modern estimation methods and models, is needed to omit the mentioned errors. ANN and LSSVM are for modeling in this research. Considering the significant part of seasonal patterns, using a preprocessing method that can extract such patterns can improve modeling; therefore, using the WT-ANN method can help.

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