TY - GEN
T1 - A Method of Garbage Quantity Prediction Based on Population Change
AU - Yu, Qiumei
AU - Wan, Hongjie
AU - Ma, Junchen
AU - Li, Huakang
AU - Sun, Guozi
N1 - Publisher Copyright:
© 2022, IFIP International Federation for Information Processing.
PY - 2022
Y1 - 2022
N2 - Aiming at the problem that the amount of urban waste changes due to population changes and is difficult to predict, a method for predicting the amount of waste based on urban population changes is proposed. After analyzing the correlation between the urban population data of Shanghai and the annual output of garbage from 2000 to 2019, the correlation coefficient and strong correlation data items are calculated. On this basis, judge whether the original population data items meet the conditions of the grey prediction model, and determine whether it can be modeled according to the grey model. Based on the grey theory, this paper analyzes the basic situation of population changes and future population growth trend in Shanghai. Finally, the annual production of municipal solid waste in Shanghai from 2020 to 2025 is predicted based on multiple linear regression analysis. The results show that the waste production of Shanghai has shown a slow growth trend since 2019, and will not increase significantly in the natural state in recent years, which provides a reference basis for subsequent research and analysis.
AB - Aiming at the problem that the amount of urban waste changes due to population changes and is difficult to predict, a method for predicting the amount of waste based on urban population changes is proposed. After analyzing the correlation between the urban population data of Shanghai and the annual output of garbage from 2000 to 2019, the correlation coefficient and strong correlation data items are calculated. On this basis, judge whether the original population data items meet the conditions of the grey prediction model, and determine whether it can be modeled according to the grey model. Based on the grey theory, this paper analyzes the basic situation of population changes and future population growth trend in Shanghai. Finally, the annual production of municipal solid waste in Shanghai from 2020 to 2025 is predicted based on multiple linear regression analysis. The results show that the waste production of Shanghai has shown a slow growth trend since 2019, and will not increase significantly in the natural state in recent years, which provides a reference basis for subsequent research and analysis.
KW - Correlation analysis
KW - Grey prediction model
KW - Multiple linear regression
KW - Population changes
KW - Waste production
UR - http://www.scopus.com/inward/record.url?scp=85132044648&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-03948-5_43
DO - 10.1007/978-3-031-03948-5_43
M3 - Conference Proceeding
AN - SCOPUS:85132044648
SN - 9783031039478
T3 - IFIP Advances in Information and Communication Technology
SP - 536
EP - 548
BT - Intelligent Information Processing XI - 12th IFIP TC 12 International Conference, IIP 2022, Proceedings
A2 - Shi, Zhongzhi
A2 - Zucker, Jean-Daniel
A2 - An, Bo
PB - Springer Science and Business Media Deutschland GmbH
T2 - 12th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2022
Y2 - 27 May 2022 through 30 May 2022
ER -
