Forecasting municipal waste accumulation rate and personal consumption expenditures using vector autoregressive (VAR) model

• Autorzy: Bień Jurand

Identyfikatory

DOI

10.30657/pea.2022.28.17

• Języki publikacji: EN

Abstrakty

EN

Accurate forecasting of municipal solid waste (MSW) generation is important for the planning, operation and optimization of municipal waste management system. However, it’s not easy task due to dynamic changes in waste volume, its composition or unpredictable factors. Initially, mainly conventional and descriptive statistical models of waste generation forecasting with demographic and socioeconomic factors were used. Methods based on machine learning or artificial intelligence have been widely used in municipal waste projection for several years. This study investigates the trend of municipal waste accumulation rate and its relation to personal consumption expenditures based on the yearly data achieved from Local Data Bank (LDB) driven by Polish Statistical Office. The effect of personal consumption expenditures on the municipal waste accumulation rate was analysed by using the vector autoregressive model (VAR). The results showed that such method can be successfully used for this purpose with an approximate level of 2.3% Root Mean Square Error (RMSE).

Słowa kluczowe

EN

waste accumulation rate; consumption expenditures; forecasting; time-series analysis; multivariate time series models; vector autoregression model

PL

wskaźnik akumulacji odpadów; wydatki konsumpcyjne; prognozowanie; analiza szeregów czasowych; wielowymiarowe szeregi czasowe; model autoregresji wektorowej

• Wydawca: Oficyna Wydawnicza Stowarzyszenia Menedżerów Jakości i Produkcji
• Czasopismo: Production Engineering Archives
• Rocznik: 2022
• Tom: Vol. 28, Iss. 2
• Strony: 150--156
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Bień Jurand

• Czestochowa University of Technology, Faculty of Infrastructure and Environment, Dabrowskiego73, 42-200 Czestochowa, Poland

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).