Assessing the Impact of Garbage Classification on China’s Economic Environment


Assessing the Impact of Garbage Classification on China’s Economic Environment


Baogang Song1*, Xing Li2, Weiming Jing3, Qian Zhang4

1College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang, 443002, China. 2College of Mechanical & Power Engineering, China Three Gorges University, Yichang, 443002, China. 3College of Computer & Information Technology, China Three Gorges University, Yichang, 443002, China. 4College of Arts & Communication, China Three Gorges University, Yichang, 443002, China.


Journal of Modern Economy

This article mainly studies the impact of waste classification on China’s economy and environment. For the economy, the annual per capita waste removal volume, waste disposal cost, and waste disposal profit from 2008 to 2017 were selected as the three input indicators, and GDP was used as the output value. A BP neural network model based on GM (1,1) was established. The GM (1,1) model is used to predict the values of the three indicators in the next five years. The relationship between GDP and the three input indicators is determined using the BP neural network. The three indicators are substituted into the model to obtain the GDP in the next five years. value. As for the environment, the number of resource processing plants, resource processing capacity, and resource processing capacity are selected as three input indicators, and the per capita green space area is used to measure the impact on the environment. The same method is used to predict the per capita public green area in the next five years. The results show that garbage classification will have a beneficial impact on China’s economy and environment, but the impact will weaken year by year.


Keywords: Garbage classification; Gray prediction; BP neural network

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How to cite this article:
Baogang Song, Xing Li, Weiming Jing, Qian Zhang. Assessing the Impact of Waste Classification on China’s economic environment Based on Gray Prediction and BP Neural Network Model. Journal of Modern Economy, 2020; 4:12. DOI: 10.28933/jme-2020-04-1005


References:

1. Shuwen Wang, Jiali Wang, Hui Wang. Analysis on the impact of “foreign garbage” on China’s ecological environment and customs risk management and control [J]. China Population, Re-sources and Environment, 2016, 26 (05): 22-31.
2. Jun Zhang, Hongping Xie, Dong Zhang, Ting Liu. Research on Cost Risk Evaluation of Transmission and Transformation Projects Based on Multistage Fuzzy Mathematics and Entropy Weight Method [J]. Shaanxi Electric Power, 2015, 43 (10): 62-67.
3. Wei Li, Hui Yang. Application of CCR model with non-Archimedean infinitesimal ε [J]. Journal of Tongren University, 2015, 17 (04): 165-167.
4. Ran Qin. Prediction of mine gas emission based on BP neural network based on principal component analysis [D]. Beijing Jiaotong University, 2015.
5. Pei Yao, Xibo Liu, Ming Li. Quantitative evaluation of the influence of Shanghai World Expo [J]. Mathematics in Practice and Theory, 2011, 41 (12): 39-46.
6. Wenju Yang. Dynamic Environmental Performance of Industries in China: An Empirical Analysis Based on DEA [J]. Journal of Quantitative & Technical Economics, 2009, 26 (06): 87-98 + 114.
7. Ying Cao, Dong Cao. Research on China’s Environmental Performance Evaluation Index System and Evaluation Method [J]. Environmental Protection, 2008 (14): 36-38.
8. Zhiqiang Zhang, Maoqi Wang, Wen Shang, Zheng Wang, Feng Deng, Shili Jiang, Renjun Wei, Qunming Chen, Jiawei Wang. Application of multi-level fuzzy mathematics comprehensive evaluation model to evaluate and compare the implementation status of “food factory hygiene standards” [J]. Journal of Food Hygiene, 1996 (01): 8-13 + 47.
9. Changling Jia. Mathematical model of multi-level fuzzy mathematics comprehensive evaluation and its application in separation machinery [J]. Journal of Huainan University of Mining and Technology, 1988 (03): 92-101.
10. China Urban Hygiene Association. Development Report of China’s Domestic Waste Treatment Industry [Z]. 2017—10
11. Science and Technology Network. Performance Evaluation of Chinese Municipal Solid Waste [Z]. 2018—01
12. Beijing Environmental Protection Bureau. 2010 Beijing Environmental Status Bulletin [Z] .2010