Presenting a data mining model based on the environmental index of sustainable urban development affected by the epidemic of Covid-19
Subject Areas :
Abbas Maleki
1
,
Sadegh Abedi
2
,
Alireza Irajpour
3
1 - Department of Industrial Management, Faculty of Management and Accounting, Qazvin Islamic Azad University, Qazvin, Iran
2 - Assistant Professor Department of Industrial Management, Faculty of Management and Accounting, Qazvin Islamic Azad University, Qazvin, Iran
3 - Assistant Professor, Department of Industrial Management, Qazvin Branch, Islamic AzadUniversity, Qazvin, Iran.
Keywords: Air Pollution, Covid-19, Data Mining, Sustainable Development, Traffic restriction,
Abstract :
In response to the Covid-19 pandemic, governments around the world have imposed severe traffic restrictions and presented different scenarios to reduce emissions from traffic sources. By applying the traffic restrictions caused by the Covid-19 epidemic, it was expected to see changes in the concentrations of air pollutants. Therefore, it was decided that the changes of air pollutants as one of the subsets of the environmental index of sustainable urban development during the covid-19 epidemic will be investigated. For this purpose, the aforementioned data are first collected in the four metropolitan cities: Tehran, Karaj, Ahvaz and Tabriz, and then processed and cleaned. After that, a proposed algorithm based on machine learning methods is presented. Machine learning methods: decision tree, random forest, support vector machine, Bayesian network and perceptron neural network are applied to the selected features. Investigations showed that the prediction model using decision tree and random forest had the best performance for both recall and accuracy criteria. The research results showed that the effect of restrictions on the concentration of pollutants in different cities is different. Also, the results show that, in general, the application of traffic restrictions during the epidemic period did not have a significant and noticeable effect in reducing the concentration of air pollutants. Also, the studies showed that the application of traffic restrictions and consequently the possible reduction of some air pollutants are not related to the deaths caused by Covid-19.