Selection of a Multicriteria Method for Selecting Independent Variables for Forecasting the Energy Potential of Municipal Waste—A Case Study in Poland

Abstract

The study examined the usefulness of selected classification methods and independent variable selection (conditional attributes) for building a model based on rough set theory (RST). The aim of the study was to estimate the local indicator of municipal waste generation and the energy potential of the waste, which could be utilized in thermal waste treatment facilities. The research was conducted on a group of 2451 municipalities in Poland which differed from each other in terms of administrative type (urban, urban–rural, and rural municipalities). These municipalities were described using 4 qualitative variables and 27 quantitative variables available in statistical reports. Using five submethods of variable classification, sets of features characterizing them in terms of the amount of municipal waste produced were extracted from the collected data. Purposeful selection of conditional attributes for modeling the unitary municipal waste accumulation index allows for reducing the number of decision variables without compromising the quality of the model. During the analysis, the number of conditional attributes was reduced from 31 to 3 for urban municipalities, 5 for urban–rural municipalities, and 7 for rural municipalities. The analysis results showed that the developed models exhibited mean absolute error (MAE) values ranging from 30 kg·(per·year)−1 to 52 kg·(per·year)−1, while the mean absolute percentage error (MAPE) ranged from 9% to 21%. By utilizing municipal waste for energy purposes, an average of approximately 160 kWh·(per·year)−1 for rural municipalities and around 270 kWh·(per·year)−1 for urban municipalities can be obtained.