Using backpropagation to predict drought factor in Keetch-Byram drought index
العناوين الأخرى
استخدام خوارزمية الانتشار الخلفي للتنبؤ بعامل الجفاف في مؤشر للجفاف Keetch-Byram
المؤلفون المشاركون
المصدر
الناشر
جامعة بغداد كلية العلوم للبنات
تاريخ النشر
2019-06-30
دولة النشر
العراق
عدد الصفحات
8
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص الإنجليزي
Forest fires continue to rise during the dry season and they are difficult to stop.
In this case, high temperatures in the dry season can cause an increase in drought index that could potentially burn the forest every time.
Thus, the government should conduct surveillance throughout the dry season.
Continuous surveillance without the focus on a particular time becomes ineffective and inefficient because of preventive measures carried out without the knowledge of potential fire risk.
Based on the Keetch-Byram Drought Index (KBDI), formulation of Drought Factor is used just for calculating the drought today based on current weather conditions, and yesterday's drought index.
However, to find out the factors of drought a day after, the data is needed about the weather.
Therefore, we need an algorithm that can predict the dryness factor.
So, the most significant fire potential can be predicted during the dry season.
Moreover, daily prediction of the dry season is needed each day to conduct the best action then a qualified preventive measure can be carried out.
The method used in this study is the backpropagation algorithm which has functions for calculating, testing and training the drought factors.
By using empirical data, some data are trained and then tested until it can be concluded that 100% of the data already well recognized.
Furthermore, some other data tested without training, then the result is 60% of the data match.
In general, this algorithm shows promising results and can be applied more to complete several variables supporters
نوع البيانات
أوراق مؤتمرات
رقم السجل
BIM-891223
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Hadisuwito, A. S.& Hasan, F. H.. 2019-06-30. Using backpropagation to predict drought factor in Keetch-Byram drought index. International Conference on Computing and Informatics (7th : 2019 : Bangkok, Thailand). . Vol. 16, no. 2 (عدد خاص) (2019), pp.477-484.Baghdad Iraq : University of Baghdad College of Science for Women.
https://search.emarefa.net/detail/BIM-891223
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Hadisuwito, A. S.& Hasan, F. H.. Using backpropagation to predict drought factor in Keetch-Byram drought index. . Baghdad Iraq : University of Baghdad College of Science for Women. 2019-06-30.
https://search.emarefa.net/detail/BIM-891223
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Hadisuwito, A. S.& Hasan, F. H.. Using backpropagation to predict drought factor in Keetch-Byram drought index. . International Conference on Computing and Informatics (7th : 2019 : Bangkok, Thailand).
https://search.emarefa.net/detail/BIM-891223
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