… treatment and recycling methods of organic solid waste … , machine learning has gradually
attracted increasing attention in solving the complex problems of organic solid waste treatment. …

… application of ML techniques for MSWM, (2) had a clear description of the ML model used,
and (3) language was limited to English. Review articles, wastewater treatment, and others …

… waste. The primary purpose of this study is to analyze AI by focusing on machine learning
algorithms used in recycling … developments in machine learning used in recycling industries. …

… on the effluent water quality. The objective of this study is to establish two machine learning
… 1-day interval TN concentration of effluent from a wastewater treatment plant in Ulsan, Korea. …

… using the Bayesian approach. Guo et al. [20] used machine learning to develop two different
models for predicting the effluent total nitrogen of a wastewater treatment plant in Ulsan, …

… the reality is, there is a lot of waste. So, we are proposing an automated waste classification
problem utilizing Machine Learning and Deep Learning algorithms. The goal of this task is to …

… FS methods (filter, wrapper, and embedded methods) on … Machine Learning (ML) algorithms,
ie Artificial Neural Network (ANN), Random Forest (RF), and Gradient Boosting Machine (…

… with instrumentation (hardware), and machine learning methods as the basis for creating …
of the various stages of the wastewater treatment process. To evaluate the multidimensional …

… Smart Waste Management systems. A real-life Smart Waste Management system called the
Smart Recycling … part of the considered Smart Waste Management system since the accurate …

… biological wastewater treatment systems. In this regard, machine learning algorithms (MLAs)
have found to be advantageous to predict the uncertain performances of the treatment …