Estimating plastic waste generation using supervised time-series learning techniques in Johannesburg, South Africa.

ABSTRACT: In recent times, many investigators have delved into plastic waste (PW) research, both locally and internationally. Many of these studies have focused on problems related to land-based and marine-based PW management with its attendant impact on public health and the ecosystem. Hitherto, there have been little or no studies on forecasting PW quantities in developing countries (DCs). The key objective of this study is to provide a forecast on PW generation in the city of Johannesburg (CoJ), South Africa over the next three decades. The data used for the forecasting were historical data obtained from Statistics South Africa (StatsSA). For effective prediction and comparison, three-time series models were employed in this study. They include exponential smoothing (ETS), Artificial Neural Netwo

SUBMITTER: Ayeleru OO 

PROVIDER: S-EPMC10987939 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature