Forecasting Solid Waste Generation in Rodriguez, Rizal Using Artificial Neural Network (Ann) and Regression Analysis: An Input to Municipality’s Solid Waste Management Plan

Abstract

Accurate and reliable forecasting of metropolitan solid devastate is extremely significant for an effective solid plan for waste management. Every local government is having a constant review of measure in the implementation of its waste management program to ensure its continuous viability and importance. The aim of this paper is to recognize the several influential variables and expand an effective model for authentic forecasting of ‘MSW generation’ and offer strategic recommendations that will improve several practices that are associated with waste management practices and several policy making in Rodriguez, Rizal.Solid waste collection of the municipality from 2010-2022, the population, different households, the GDP, commercial establishments and services (CES), and the tourist arrivalfrom 2010 to 2022 were gathered. Two forecasting methods, the “Artificial Neural Network” (ANN) and the multivariable simple regression with the use of Principal Component Analysis (PCA) have been tested that is for their ability for predicting the annual waste production within the municipality. Among the five components, population, Household, and Commercial Establishments have the highest eigenvalues and it account for almost 86% of the total variance in the original data. Furthermore, these components, present the lowestp-values; to which regression model was developed. Artificial Neural Network (ANN) model was has been established through using Multilayer-perceptron Neural Network. The same factors with normalized importance were identified, the Population, Household and Commercial Establishments. Result showed that “ANN” that is Artificial Neural Network has outperformed regression analysis in predicting the solid waste generation having less quantity in terms of the root RMSE. It was also including “mean error” (ME). At the same time, it also include “mean absolute deviation” (MAD) along with “mean percentage error” (MPE). It was in terms of mean “absolute percentage error” (MAPE).A strategic measure has been recommended to enhance waste management practices and policy making of the municipality of Rodriguez that will improve the accuracy as well as effectiveness of its waste management practices and also reduce environmental impacts.