Previsão de geração de resíduos sólidos para o aterro de Aparecida de Goiânia (GO) por séries temporais

Merelles, Leonardo Rodrigues de Oliveira; Silva, Cláudio de Oliveira e; Luz, Marta Pereira da; Menezes, José Elmo de; Dias, Viviane de Souza

doi:10.1590/s1413-41522019183284

Cited by 3 publications

(1 citation statement)

References 21 publications

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“…Ghinea applied time series analysis to achieve the prediction of urban solid waste in Iasi City (Ghinea et al, 2016). Merelles analyzed the prediction of solid waste generation in landfill sites using time series analysis (Merelles et al, 2019). Wang established a time series model to predict the domestic waste generation in Hefei city, achieving a good modeling performance(P. .…”

Section: Introductionmentioning

confidence: 99%

Forecasting the amount of domestic waste clearance in Shenzhen with an optimized grey model

Zeng,

Xia,

Yang

2024

Stoch Environ Res Risk Assess

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As a leading economic center in China and an international metropolis, Shenzhen has great significance in promoting sustainable urban development. To predict its amount of domestic waste clearance, a new multivariable grey prediction model with combinatorial optimization of parameters is established in this paper. Firstly, the new model expands the value range of the order r of a grey accumulation generation operator from positive real numbers (R+) to all real numbers (R), which enlarges the optimization space of parameter and has positive significance for improving model performance. Secondly, the dynamic background-value coefficient λ is introduced into the new model to improve the smoothing effect of the nearest neighbor generated sequences. Thirdly, the Particle Swarm Optimization (PSO) is employed to optimize parameters r and λ to improve the overall performance of the new model. The new model is used to simulate and predict the amount of domestic waste clearance in Shenzhen, and the comprehensive error of the new model is only 0.27%, which is far superior to several other similar models. Lastly, the new model is applied to predict the amount of domestic waste clearance in Shenzhen. The results indicate the amount of domestic waste clearance in 2028 could be 9.96 million tons, an increase of 20.58% compared to 2021.This highlights the significant challenge that Shenzhen faces in terms of urban domestic waste treatment.Therefore, some targeted countermeasures and suggestions have been proposed to ensure the sustainable development of Shenzhen's economy and society.

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Section: Introductionmentioning

confidence: 99%

Forecasting the amount of domestic waste clearance in Shenzhen with an optimized grey model

Zeng,

Xia,

Yang

2024

Stoch Environ Res Risk Assess

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System dynamics-based prediction of municipal solid waste generation in high-cold and high-altitude area: The case of Lhasa, Tibet

et al. 2022

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The ecological environment in high-cold and high-altitude area is fragile and sensitive, which raise higher claim for municipal solid waste (MSW) management. In the high-cold and high-altitude area, there are problems, such as the mismatch between the actual amount of MSW generated and the scale of transportation and treatment facilities, and the inefficiency of MSW management. In terms of MSW forecasting methods, it is also difficult to forecast due to the lack of data. This study is the first to propose a system dynamics-based method for predicting the amount of MSW generated in high-cold and high-altitude area, and apply it to Lhasa. The research results show that the total amount of MSW generated in Lhasa is small, but the growth rate is fast. Through dynamic simulation, it is found that the synergistic consideration of gross domestic product (GDP) growth rate, urban construction policy and tourism development policy can significantly reduce the growth trend (14% emission reduction in 2030). In addition, strengthening supervision and restraint, publicity and education in high-cold and high-altitude area can produce better waste sorting effects, minimise the pressure on treatment facilities, and improve resource utilisation. Finally, the policy implications are suggested, for example, in the process of MSW management, the impact of economy, urbanisation, tourism and so on, should be taken into account and comprehensively adjusted. It is anticipated that this model and policy implications can be applied to other high-cold and high-altitude cities to provide data support and policy reference for the whole-process management of MSW.

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Modeling, prediction and suggestions of the amount of domestic waste clearance in Shenzhen using an optimized high- performance grey model

Zeng,

Xia,

Yang

2023

Preprint

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As a leading economic center in China and an international metropolis, Shenzhen has great significance in promoting sustainable urban development. To predict its amount of domestic waste clearance, a new multivariable grey prediction model with combinatorial optimization of parameters is established in this paper. Firstly, the new model expands the value range of the order r of a grey accumulation generation operator from positive real numbers (R+) to all real numbers (R), which enlarges the optimization space of parameter and has positive significance for improving model performance. Secondly, the dynamic background-value coefficient λ is introduced into the new model to improve the smoothing effect of the nearest neighbor generated sequences. Thirdly, the Particle Swarm Optimization (PSO) is employed to optimize parameters r and λ to improve the overall performance of the new model. The new model is used to simulate and predict the amount of domestic waste clearance in Shenzhen, and the comprehensive error of the new model is only 0.27%, which is far superior to several other similar models. Lastly, the new model is applied to predict the amount of domestic waste clearance in Shenzhen. The results indicate the amount of domestic waste clearance in 2028 could be 9.96 million tons, an increase of 20.58% compared to 2021.This highlights the significant challenge that Shenzhen faces in terms of urban domestic waste treatment. Therefore, some targeted countermeasures and suggestions have been proposed to ensure the sustainable development of Shenzhen's economy and society.

show abstract

Previsão de geração de resíduos sólidos para o aterro de Aparecida de Goiânia (GO) por séries temporais

Cited by 3 publications

References 21 publications

Forecasting the amount of domestic waste clearance in Shenzhen with an optimized grey model

Forecasting the amount of domestic waste clearance in Shenzhen with an optimized grey model

System dynamics-based prediction of municipal solid waste generation in high-cold and high-altitude area: The case of Lhasa, Tibet

Modeling, prediction and suggestions of the amount of domestic waste clearance in Shenzhen using an optimized high- performance grey model

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