Application of Improved Naive Bayesian-CNN Classification Algorithm in Sandstorm Prediction in Inner Mongolia
المؤلفون المشاركون
Qing-dao-er-ji, Ren
Tiancheng, Li
Ying, Qiu
المصدر
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-12-06
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
Hazards of sandstorm are increasingly recognized and valued by the general public, scientific researchers, and even government decision-making bodies.
This paper proposed an efficient sandstorm prediction method that considered both the effect of atmospheric movement and ground factors on sandstorm occurrence, called improved naive Bayesian-CNN classification algorithm (INB-CNN classification algorithm).
Firstly, we established a sandstorm prediction model based on the convolutional neural network algorithm, which considered atmospheric movement factors.
Convolutional neural network (CNN) is a deep neural network with convolution structure, which can automatically learn features from massive data.
Then, we established a sandstorm prediction model based on the Naive Bayesian algorithm, which considered ground factors.
Finally, we established a sandstorm prediction model based on the improved naive Bayesian-CNN classification algorithm.
Experimental results showed that the prediction accuracy of the sandstorm prediction model based on INB-CNN classification algorithm is higher than that of others and the model can better reflect the law of sandstorm occurrence.
This paper used two algorithms, naive Bayesian algorithm and CNN algorithm, to identify and diagnose the strength of sandstorm in Inner Mongolia and found that combining the two algorithms, INB-CNN classification algorithm had the greatest success in predicting the occurrence of sandstorms.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Tiancheng, Li& Qing-dao-er-ji, Ren& Ying, Qiu. 2019. Application of Improved Naive Bayesian-CNN Classification Algorithm in Sandstorm Prediction in Inner Mongolia. Advances in Meteorology،Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1118685
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Tiancheng, Li…[et al.]. Application of Improved Naive Bayesian-CNN Classification Algorithm in Sandstorm Prediction in Inner Mongolia. Advances in Meteorology No. 2019 (2019), pp.1-13.
https://search.emarefa.net/detail/BIM-1118685
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Tiancheng, Li& Qing-dao-er-ji, Ren& Ying, Qiu. Application of Improved Naive Bayesian-CNN Classification Algorithm in Sandstorm Prediction in Inner Mongolia. Advances in Meteorology. 2019. Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1118685
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1118685
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