Abstract
Purpose
The proposed model can emphasize the priority of new information and can extract messages from the first pair of original data. The comparison results show that the proposed model can improve the traditional grey model.
Design/methodology/approach
The grey multivariate model with fractional Hausdorff derivative is firstly put forward to enhance the forecasting accuracy of traditional grey model.
Findings
The proposed model is used to predict the air quality composite index (AQCI) in ten cities respectively.
Originality/value
The effect of population density on AQCI in cities with poor air quality is not as significant as that of the cities with better air quality.
Subject
Computer Science (miscellaneous),Social Sciences (miscellaneous),Theoretical Computer Science,Control and Systems Engineering,Engineering (miscellaneous)
Reference49 articles.
1. SARIMA damp trend grey forecasting model for airline industry;Journal of Air Transport Management,2020
2. An envelopment learning procedure for improving prediction accuracies of grey models;Computers and Industrial Engineering,2020
3. Fractional Hausdorff grey model and its properties;Chaos, Solitons and Fractals,2020
4. The influence of increased population density in China on air pollution;Science of the Total Environment,2020
5. Examining the impact of demographic factors on air pollution;Population and Environment,2004
Cited by
8 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献