مدل داده‌کاوی مبتنی بر یادگیری ماشین جهت پیش‌بینی آلودگی هوا در کلان‌شهرهای ایران
محورهای موضوعی : آلودگی های محیط زیست
عباس ملکی
1
(گروه مدیریت صنعتی، دانشکده مدیریت و حسابداری، دانشگاه آزاد اسلامی واحد قزوین، قزوین، ایران)
صادق عابدی
2
(استادیار گروه مدیریت صنعتی، دانشکده مدیریت و حسابداری، دانشگاه آزاد اسلامی، واحد قزوین، قزوین، ایران)
علیرضا ایرج پور
3
(استادیار گروه مدیریت صنعتی، دانشکده مدیریت و حسابداری، دانشگاه آزاد اسلامی، واحد قزوین، قزوین، ایران)
کلید واژه: پیش بینی آلودگی هوا, کلان‌شهرهای ایران, یادگیری ماشین, شبکه عصبی, کووید-19,
چکیده مقاله :
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Introduction: In response to the Covid-19 pandemic, governments around the world have imposed severe restrictions and presented different scenarios of reducing emissions from traffic sources. With the application of traffic restrictions due to the covid-19 epidemic and quarantine, it seemed that there was a reduction in the traffic of vehicles and the concentration of pollutants and the air quality index approached the quality standards. Therefore, it was expected to see changes in the concentration of CO, O3, NO, NO2, NOx, SO2, PM2.5 and PM10 pollutants, which are pathogenic factors and sometimes premature death. Materials and Methods: Using the data mining method, in the first stage, the change in the concentration of pollutants in the period of the Covid-19 epidemic compared to the period before it is investigated in order to determine what effect the application of traffic restrictions has on the change in the concentration of pollutants in each from the metropolises of Tehran and Shiraz. In the second stage, predictive models are presented using feedforward and deep neural networks to predict the level of health importance based on the application of each of the traffic restrictions in each metropolis. |
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Results and Discussion: This study shows that the change in the concentration of pollutants during the covid-19 era is different compared to before, in the cities of Tehran and Shiraz; In such a way that the concentration of most pollutants increased in Tehran metropolis and decreased in Shiraz metropolis. According to the result obtained and the difference in the process of changing the concentration of pollutants, in order to control the air quality index, predictive models were presented for each metropolis. Conclusion: For pollutants, the same increasing or decreasing pattern is not seen in the studied metropolises, so it can be said that the effect of the same restrictions on changing the concentration of pollutants is different in different cities; Therefore, applying the same restrictions in all cities does not necessarily lead to a reduction in pollution, and for each urban and environmental situation, a model of traffic restrictions specific to that situation should be prepared. |
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