Prediction of Urban Waste Disposal Based on ARIMA Model

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The amount of municipal solid waste(MSW)transportation has become an important basis of handling urban domestic waste, at the same time, accurate predictions of time series data have motivated the researchers to develop innovative models for urban solid waste management.Therefore, predicting the MSW transportation amount in a scientific manner is one of the most essential parts of the urban waste management work. Based on the raw data of MSW transportation amount from 1993 to 2012 of Wuhan city, the capital of Hubei province, this paper chose Autoregressive Integrated Moving Average Model(also called ARIMA model), used Eviews software to process the data and test various effective inspection, then made a prediction of the amount of MSW transportation of Wuhan, and got access to the conclusions through comparing the original data and predicted one. The results showed that the predicted value of the amount of MSW transportation in 2013 was consistent with the original one, and would reach 214.82 wt in 2014. The results also demonstrated that, the MSW transportation amount prediction based on ARIMA model is practicable due to its high applicability and accuracy, offering decisive information for the urban environmental planning and urban domestic waste controlling.

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Periodical:

Edited by:

Jinhui Li and Hualong Hu

Pages:

707-713

DOI:

10.4028/www.scientific.net/AMM.768.707

Citation:

Y. Yu et al., "Prediction of Urban Waste Disposal Based on ARIMA Model", Applied Mechanics and Materials, Vol. 768, pp. 707-713, 2015

Online since:

June 2015

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$35.00

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[1] T. Yu, T. Huang, Y.X. Pan, L.H. Yang,L. Wang, Comprehensive urban waste disposal forecasting model based on the BP artificial neural network and grey relational degree, Journal of Safety and Environment, 13(2013)94-97.

[2] G.Y. Chen, Y.G. Zhang, J.J. Zeng, Forecasting municipal solid waste production by Gray system theory in China, Enviromental Protection Science, 37(2011)29-32.

[3] J.L. Deng, The grey system theory, Huazhong University of Science and Technology Press, Wuhan, P.R. China, (1990).

[4] W.M. Wang, D. Liu, An improved method for predicting the output of municipal solid waste, Sichuan Environment, 24(2005)106-108, 114.

[5] Wuhan Environmental Quality Report from 2001 to 2005, Wuhan Environmental Protection Bureau, Wuhan P.R. China, (2006).

[6] Wuhan Statistical Yearbook, Bureau of Statistics of Wuhan, Wuhan P.R. China, (2013).

[7] George E.P. Box, Gwilym M. Jenkins, Gregory C. Reinsel, Time Series Analysis: Forecasting and Control, forth ed., China Machine Press, (2011).

DOI: 10.1002/9781118619193.ch5

[8] Y. Zhou, Time series model of China civil aeronautic cargo capacity, Journal of Chengdu University of Technology(Science&Technology Edition), Sichuan P.R. China, 32(2005)433-437.

[9] Y. Yu, Y.J. Huang, J.H. He, J.H. Zhao, Influencing factors determination of MSW clearence volume Based on Spatial Dependency Consideration, Advanced Materials Research, 878(2014) pp.513-519.

DOI: 10.4028/www.scientific.net/amr.878.513

[10] X.Z. Song, Z.X. Wang, Stock Liquidity and Asset Pricing: Empirical Analysis from the Perspective of Time-Series Regression, The Theory and Practice of Finace and Economics, 25(2004)43-39.

[11] Y. Wang, Applied Time Series Analysis, Beijing: China Renmin University Press, (2005).

[12] Z.M. Feng, Y.Z. Yang, D. Zhang, Y. Tang, Natural environment suitability for human settlements in China based on GIS, J. Geogr. Sci. 19 (2009) : 437-446.

DOI: 10.1007/s11442-009-0437-x

[13] J.H. Chen, X.Y. Yong, S. Yang, L. Liu, Analysis and Forecast About Mineral Product Price Based on Time Series Model, Science and Technology, 34(2009): 13-14.

[14] L.L. Wu, J.W. Lu, L. Liao, J.S. Jiang, Prediction of Domestic Waste Output Based on ARIMA Model, Environmental Sanitation Engineering, 21(2013): 2-3.

[15] J. Hassan, ARIMA and regression models for prediction of daily and monthly clearness index, Renewable Energy, 68(2014): 421-427.

DOI: 10.1016/j.renene.2014.02.016

[16] L. Wu, L. Liao, Study on MSW Delivering Quantity Forecasting and Developing Directions of Disposal Technology, (2007).

[17] Office of Solid Waste Emergency Response, USEPA, Municipal solid waste in the United States:2001 facts and fingures executive summary, USA: Office of Solid Waste Emergency Response, USEPA, (2003).

[18] W.P. Du, Q.X. Gao, E.C. Zhang, Q.L. Miao, J.G. Wu, The Treatment and Trend Analysis of Municipal Solid Waste in China, 19(2006): 116-117.

[19] Boland J. Time series and statistical modeling of solar radiation. In: Badescu Viorel, editor. Recent advances in solar radiation modeling. Springer-Verlag, 2008, pp, 283-312.

DOI: 10.1007/978-3-540-77455-6_11

[20] Lutkepohl H, Kratzig M. Applied time series econometrics. Cambridge, UK: Cambridge University Press, (2004).

[21] G.P. Zhang, Time series forecasting using a hybrid ARIMA and neural network model, Neuro computing, 50(2003): 159-175.

DOI: 10.1016/s0925-2312(01)00702-0

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