Waste Generation Forecast and Prediction Analysis using Exponential Smoothing Model
Olufemi Adebayo Oroye, Jeremiah V. Akintade, Beauty E. Oroye · 2024
The escalating global concern regarding waste generation underscores the need for a comprehensive understanding and modeling of this phenomenon in order to optimize waste management operations. Inadequate waste management operations not only detract the aesthetic appeal of cities such as Lagos State but also present significant health risks and environmental hazards. In order to mitigate this, accurate prediction plays a vital role in strategic waste management planning and processes. This study utilizes exponential smoothing models (i.e., seasonal exponential smoothing model and winter exponential smoothing method) to forecast waste generation in Eti Osa Local Government Area of Lagos State and also predicted the number of waste fleets needed. The result of using both aforementioned exponential smoothing models was compared to determine the most suitable modeling method for waste generation prediction and planning. Monthly data between January 2019 and December 2023 of waste generated in Eti Osa Local Government Area was obtained from Lagos State Waste Management Authority. The finding revealed that the seasonal exponential smoothing model emerges as the most suitable choice for forecasting waste generation. Based on the result of the monthly waste generation forecasted for the year 2024, the required amount of fleet needed per month was also predicted. Thus, the seasonal exponential smoothing model can be used to estimate Lagos State's future monthly waste generation quantity to plan a more efficient, cost-effective, and sustainable waste management plan.