Title: Forecasting solid waste generation: a Fourier series approach

Authors: Disraeli Asante-Darko; Emmanuel Sarkodie Adabor; Samuel Kwame Amponsah

Addresses: Business School, Ghana Institute of Management and Public Administration, P.O. Box AH 50, Achimota, Accra, Ghana ' School of Technology, Ghana Institute of Management and Public Administration, P.O. Box AH 50, Achimota, Accra, Ghana ' Department of Mathematics, Kwame Nkrumah University of Science and Technology, Private Mail Bag, University Post Office, KNUST, Kumasi, Ghana

Abstract: Successful planning of a solid waste management system depends on the accuracy of prediction of solid waste generation. With a continual economic development and increase in the living standards, the demand for goods and services is increasing at an unprecedented rate, resulting in a commensurate increase in per capita waste generation. In order to facilitate informed decision making for an effective solid waste management, we propose a Fourier Series Model to forecast solid waste generation in Kumasi, Ghana. A monthly waste data from 2007 to 2014 was obtained from the solid waste department of the Kumasi Metropolitan Assembly, Ghana. This was used to formulate the Fourier series model for forecasting solid waste. This novel application incorporates the characteristics of the data making them it appropriate for forecasting solid waste. MAPE and RMSE comparison of our proposed model with existing method for forecasting solid waste shows that our method competes favourably well.

Keywords: solid waste; Fourier series; waste management; forecasting; mean absolute percentage error; MAPE; root mean squared error; RMSE.

DOI: 10.1504/IJEWM.2017.084640

International Journal of Environment and Waste Management, 2017 Vol.19 No.4, pp.318 - 337

Received: 04 Apr 2016
Accepted: 05 Jan 2017

Published online: 19 Jun 2017 *

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