Study on the Model of CPI Prediction Based on BP Neural Network

Hu, Wang; Fan, Gengyao

doi:10.1109/itcs.2010.147

Cited by 3 publications

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“…The core variable is per capita GDP. In order to eliminate the impact of prices, the per capita GDP of each city is converted into the actual per capita GDP with 2009 as the base year (Wang et al 2010). The variable data is also collected from the China Urban Construction Statistical Yearbook.…”

Section: Explanation Of Variables and Data Sourcesmentioning

confidence: 99%

Archives of Environmental Protection

Yang,

Wang,

et al. 2022

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Since the implementation of the compulsory sorting of domestic waste policy in China, the participation rate of residents is low, which leads to the unsatisfactory result of terminal reduction of domestic waste. Therefore, the problem of domestic waste reduction still needs to rely on source reduction. Based on the panel data of 29 provincial capitals in China from 2009 to 2018, this study conducts a comprehensive threshold effect test on per capita GDP and other influencing factors of domestic waste production, conducts panel threshold regression for the factors with threshold value, and explores the nonlinear relationship between per capita GDP and domestic waste production under the influence of different threshold variables. The results show that when the urban population density is less than 272 people/km 2 , the increase of 1% of per capita GDP will lead to a decrease of 0.251% in the domestic waste production, otherwise, it will lead to an increase of 0.249%; when the per capita consumption expenditure is less than the threshold value of 10,260 yuan/year, the influence coefficient of per capita GDP is 0.155, which increases to 0.207 above the threshold. When the share of tertiary industry is taken as the threshold variable, the two threshold values are 61% and 71% respectively. Through the analysis of control variables, it has been found that population size and amount of courier per capita have significant positive effects on domestic waste production, while gas permeability and the number of non-governmental organizations have significant negative effects.

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Section: Explanation Of Variables and Data Sourcesmentioning

confidence: 99%

Archives of Environmental Protection

Yang,

Wang,

et al. 2022

View full text Add to dashboard Cite

show abstract

Study on the Model of CPI Prediction Based on BP Neural Network

Cited by 3 publications

References 0 publications

Archives of Environmental Protection

Archives of Environmental Protection

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