基于灰色预测模型的江西省生活垃圾清运量预测研究

Introduction

With the rapid development of urbanization, the amount of urban domestic waste has been increasing year by year. The disposal of domestic waste has become a hot topic of concern for society. The effective management and disposal of domestic waste is not only related to the environmental protection and public health, but also to the sustainable development of the society. Therefore, it is necessary to predict the amount of domestic waste in order to make effective arrangements for domestic waste disposal.

In this paper, we use the grey prediction model to predict the amount of domestic waste in Jiangxi province in the next five years based on the analysis of the data of the past ten years.

Basic situation of urban domestic waste

Urban domestic waste refers to the solid waste generated by residents' daily life, including household garbage, kitchen waste, garden waste, etc. With the rapid development of urbanization, the amount of domestic waste has been increasing year by year. In 2018, the total amount of domestic waste in China was 22.4 billion tons, with an average of 0.8 kg per person per day. Among them, the amount of household garbage was about 200 million tons, accounting for about 9% of the total amount of domestic waste.

As for Jiangxi province, the total amount of domestic waste increased from 5.81 million tons in 2010 to 9.86 million tons in 2019, with an average annual growth rate of 5.15%. The per capita domestic waste increased from 0.43 kg/day in 2010 to 0.68 kg/day in 2019.

Research status at home and abroad

Domestic waste prediction is a hot topic in the field of environmental science. Many scholars have carried out research on domestic waste prediction based on different methods.

At present, the commonly used methods for domestic waste prediction include regression analysis, time series analysis, artificial neural network, grey prediction model, etc. Among them, the grey prediction model has the advantages of simple calculation, small data requirements, and good prediction accuracy, and has been widely used in the field of domestic waste prediction.

Model establishment and mathematical calculation process

The grey prediction model is a method of predicting the future trend of a system based on the existing data of the system, which is suitable for prediction of systems with small samples, incomplete data, and uncertain development trends. The main steps of the grey prediction model are: data processing, model establishment, model verification, and prediction.

In this paper, we use the GM(1,1) grey prediction model to predict the amount of domestic waste in Jiangxi province in the next five years. The specific steps are as follows:

Data preprocessing: The original data of the domestic waste in Jiangxi province from 2010 to 2019 is preprocessed to obtain the accumulated data.
Establish the GM(1,1) model: Use the accumulated data to establish the GM(1,1) grey prediction model.
Model verification: Verify the accuracy of the established model through the residual test and the grey correlation degree test.
Prediction: Use the established model to predict the amount of domestic waste in Jiangxi province from 2020 to 2024.

Conclusion

In this paper, we use the grey prediction model to predict the amount of domestic waste in Jiangxi province in the next five years. Through the data analysis and model establishment, it is found that the amount of domestic waste in Jiangxi province will continue to increase in the next five years, with an average annual growth rate of 4.51%, and the amount of domestic waste in 2024 will reach 12.1 million tons. This prediction provides a scientific basis for the government to make effective arrangements for domestic waste disposal and management.