Applying machine learning approach in recycling
Erkınay Özdemir, Merve
MetadataShow full item record
Erkinay Ozdemir, M., Ali, Z., Subeshan, B., & Asmatulu, E. (2021). Applying machine learning approach in recycling. Journal of Material Cycles and Waste Management, doi:10.1007/s10163-021-01182-y
Waste generation has been increasing drastically based on the world’s population and economic growth. This has signifcantly afected human health, natural life, and ecology. The utilization of limited natural resources, and the harming of the earth in the process of mineral extraction, and waste management have far exceeded limits. The recycling rate are continuously increasing; however, assessments show that humans will be creating more waste than ever before. Some difculties during recycling include the signifcant expense involved during the separation of recyclable waste from non-disposable waste. Machine learning is the utilization of artifcial intelligence (AI) that provides a framework to take as a structural improvement of the fact without being programmed. Machine learning concentrates on the advancement of programs that can obtain the information and use it to learn to make future decisions. The classifcation and separation of materials in a mixed recycling application in machine learning is a division of AI that is playing an important role for better separation of complex waste. The primary purpose of this study is to analyze AI by focusing on machine learning algorithms used in recycling systems. This study is a compilation of the most recent developments in machine learning used in recycling industries.
Click on the DOI link to access the article (may not be free).