Atliekų kiekio prognozavimo sistema – rodiklius veikiančių veiksnių Lietuvoje tyrimas

Davidavičienė, Vida; Janeliūnienė, Rasma; Liberytė, Ginta

doi:10.3846/btp.2012.14

Cited by 2 publications

(1 citation statement)

References 34 publications

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“…The forecasting methods used for different types of waste predictions include machine learning (Kontokosta et al, 2018), small area estimation (Kontokosta et al, 2018), artificial neural networks (Akgül et al, 2020;Cubillos, 2020;Hao et al, 2019), regression analysis (Ghinea et al, 2016;Davidavičiene et al, 2012;Pavlas et al, 2020;Wei et al, 2013), ARIMA (Buhl et al, 2020;Ghinea et al, 2016;Ghomi & Marandi, 2016;Mwenda et al, 2014), artificial intelligence (Abbasi & Hanandeh, 2016), multivariate grey models (Intharathirat et al, 2015), Holt's double Exponential Smoothing (Islam & Huda, 2019), Holt-Winters Exponential Smoothing (Wąsik & Chmielowski, 2016), Winters multiplicative methods (Denafas et al, 2014).…”

Section: Methodsmentioning

confidence: 99%

Trends of Municipal Waste Flows, Composition, Treatment in Lithuania and Its Regions

Stankevičienė

Bužinskė

2021

International Scientific Conference „Contemporary Issues in Business, Management and Economics Engineering"

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Purpose – to propose conceptual model for forecasting of waste trends and empirically implement the model based on the case of Lithuania and its regions. Research methodology – 1) scientific literature analysis on circular economy, zero waste and waste management, 2) gathering of statistical data on waste flows, composition and treatment 3) creation of conceptual model of forecasting with Exponential Smoothing for prediction of waste-related trends based on literature review. Findings – proposed conceptual model for prediction of waste-related trends is adequate for prognosis of waste flows, composition and treatment ways. The main forecasting results are that the total waste flows will increase in Lithuania, on a regional level, Alytus, Kaunas, Klaipėda, Telšiai, have a tendency of the increase in municipal waste flows. The results imply that in order to contribute to the reduction of waste, the active involvement on a regional level is necessary. Research limitations – the research can be extended with statistical data on waste of other countries to check adequacy of the conceptual model for waste-related trends prognosis. Practical implications – the findings of the research can be applied in planning and decision-making process of gov-ernment bodies on national or local level. The results are also useful for the general public in educational purposes. Originality/Value – the study provides original conceptual model for the forecasting of waste-related trends which provides robust results of predictions and can be replicated by different countries.

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