Open AccessResearch on Industrial Hazardous Waste Generation in China Based on Combination Forecasting Model
Author(s) -
Xuedong Liang,
Fuhai Yan,
Xu Yang
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/505/1/012032
Subject(s) - hazardous waste , autoregressive integrated moving average , industrial production , production (economics) , engineering , computer science , time series , waste management , economics , machine learning , keynesian economics , macroeconomics
As the largest developing country, with the rapid development of society and economy, China’s industrial hazardous waste generation is constantly increasing.. In order to promote the scientific and effective management of industrial hazardous wastes, it is necessary to carry out reliable prediction research on industrial hazardous wastes generation. In view of the analysis of existing studies, firstly, this article considers the trend model, gray model, support vector machine model, and ARIMA model based on the sample data amount and the applicability of the prediction method to predict the hazardous waste production data separately; Then, the entropy weight method is used to evaluate independent models through multiple error indicators to determine the combined weight of each independent model; Finally, a combination forecasting model was established to study the production of industrial hazardous waste, and the application of the combination forecasting model to the forecast of industrial hazardous waste production in China was explored.