Atmospheric PM2.5 Concentration Prediction Based on Time Series and Interactive Multiple Model Approach
المؤلفون المشاركون
Li, Xiao-Li
Li, Jihan
Wang, Kang
المصدر
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-10-15
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Urbanization, industrialization, and regional economic integration have developed rapidly in China in recent years.
Air pollution has attracted more and more attention.
However, PM2.5 is the main particulate matter in air pollution.
Therefore, how to predict PM2.5 accurately and effectively has become a concern of experts and scholars.
For the problem, atmosphere PM2.5 concentration prediction algorithm is proposed based on time series and interactive multiple model in this paper.
PM2.5 concentration is collected by using the monitor at different air quality levels.
The time series models are established by historical PM2.5 concentration data, which were given by the autoregressive model (AR).
In the paper, three PM2.5 time series models are established for three different air quality levels.
Then, the three models are converted to state equation, respectively, by autoregressive integrated with Kalman filter (AR-Kalman) approaches.
Besides, the proposed interactive multiple model (IMM) algorithm is, respectively, compared with autoregressive (AR) model algorithm and AR-Kalman prediction algorithm.
It is turned out the proposed IMM algorithm is more accurate than the other two approaches for PM2.5 prediction, and it is effective.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Li, Jihan& Li, Xiao-Li& Wang, Kang. 2019. Atmospheric PM2.5 Concentration Prediction Based on Time Series and Interactive Multiple Model Approach. Advances in Meteorology،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1118517
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Li, Jihan…[et al.]. Atmospheric PM2.5 Concentration Prediction Based on Time Series and Interactive Multiple Model Approach. Advances in Meteorology No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1118517
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Li, Jihan& Li, Xiao-Li& Wang, Kang. Atmospheric PM2.5 Concentration Prediction Based on Time Series and Interactive Multiple Model Approach. Advances in Meteorology. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1118517
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1118517
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر