Open AccessApplication of machine learning algorithms in municipal solid waste management: A mini review
Author(s) -
Wanjun Xia,
Yanping Jiang,
Xiaohong Chen,
Rui Zhao
Publication year - 2021
Publication title -
waste management and research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.713
H-Index - 80
eISSN - 0734-242X
pISSN - 1096-3669
DOI - 10.1177/0734242x211033716
Subject(s) - municipal solid waste , urbanization , engineering , algorithm , sustainable development , population , environmental planning , computer science , waste management , environmental science , economic growth , political science , economics , demography , sociology , law
Population growth and the acceleration of urbanization have led to a sharp increase in municipal solid waste production, and researchers have sought to use advanced technology to solve this problem. Machine learning (ML) algorithms are good at modeling complex nonlinear processes and have been gradually adopted to promote municipal solid waste management (MSWM) and help the sustainable development of the environment in the past few years. In this study, more than 200 publications published over the last two decades (2000–2020) were reviewed and analyzed. This paper summarizes the application of ML algorithms in the whole process of MSWM, from waste generation to collection and transportation, to final disposal. Through this comprehensive review, the gaps and future directions of ML application in MSWM are discussed, providing theoretical and practical guidance for follow-up related research.