FORECASTING THE MORPHOLOGICAL COMPOSITION OF MUNICIPAL WASTE IN THE DESIGN THE CITY SANITARY SCHEME

Abstract

The article substantiates the importance of predicting the morphological composition of solid waste. For the forecasting study, initial data were collected by surveying the residents of Vinnytsia. This study made it possible to predict the impact on the morphological composition of MSW of a number of factors: seasonality factors, external influences, socio-behavioral factors, consumer behavior and personal preferences, living conditions, organizational factors. A correlation was found between the factors and the target variables of forecasting allows to predict the change in the morphological composition of municipal solid waste depending on the socio-domestic changes in the lives of urban citizens.A model for predicting the morphological composition of municipal solid waste was proposed. This prediction model is based on the artificial neural network method. It makes it possible to analyze the ratio of fractions of municipal solid waste produced in a particular household. The choice of an artificial neural network is due to its ability to predict several indicators. The fractions that were predicted are glass, paper and cardboard, plastic of various markings, the fraction of combined packaging, metal and the fraction of non-recyclable waste.The practical implementation of forecasting the morphological composition of solid waste is performed on the example of Vinnytsia. Based on the information obtained by predicting the morphological composition of solid waste, the prospects for the formation of different fractions of solid waste in the city are practically calculated.Developed forecasting can be an effective tool for management decisions on the location of sanitation facilities, by estimating data on the volumes of different fractions produced in different areas.