Comparative Analysis of the Implementation of Support Vector Machines and Long Short-Term Memory Artificial Neural Networks in Municipal Solid Waste Management Models in Megacities

Johanna Karina Solano Meza (), David Orjuela Yepes, Javier Rodrigo-Ilarri and María-Elena Rodrigo-Clavero
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Johanna Karina Solano Meza: Department of Environmental Engineering, Santo Tomás University, Road 9 Street 51-11, Bogotá 110231, Colombia
David Orjuela Yepes: Department of Environmental Engineering, Santo Tomás University, Road 9 Street 51-11, Bogotá 110231, Colombia
Javier Rodrigo-Ilarri: Instituto de Ingeniería del Agua y Medio Ambiente (IIAMA), Universitat Politècnica de València, 46022 Valencia, Spain
María-Elena Rodrigo-Clavero: Instituto de Ingeniería del Agua y Medio Ambiente (IIAMA), Universitat Politècnica de València, 46022 Valencia, Spain

IJERPH, 2023, vol. 20, issue 5, 1-20

Abstract: The development of methodologies to support decision-making in municipal solid waste (MSW) management processes is of great interest for municipal administrations. Artificial intelligence (AI) techniques provide multiple tools for designing algorithms to objectively analyze data while creating highly precise models. Support vector machines and neuronal networks are formed by AI applications offering optimization solutions at different managing stages. In this paper, an implementation and comparison of the results obtained by two AI methods on a solid waste management problem is shown. Support vector machine (SVM) and long short-term memory (LSTM) network techniques have been used. The implementation of LSTM took into account different configurations, temporal filtering and annual calculations of solid waste collection periods. Results show that the SVM method properly fits selected data and yields consistent regression curves, even with very limited training data, leading to more accurate results than those obtained by the LSTM method.

Keywords: artificial neural networks; municipal solid waste; support vector machines; solid waste management; waste disposal (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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