دورية أكاديمية

Prediction of Severe Thunderstorms applying Neural Network using RSRW Data

التفاصيل البيبلوغرافية
العنوان: Prediction of Severe Thunderstorms applying Neural Network using RSRW Data
المؤلفون: Himadri Chakrabarty, Sonia Bhattacharya, Panihati Mahavidyalaya
المساهمون: The Pennsylvania State University CiteSeerX Archives
المصدر: http://research.ijcaonline.org/volume89/number16/pxc3894362.pdfTest.
المجموعة: CiteSeerX
مصطلحات موضوعية: General Terms Pattern Recognition, Squall, Mesoscale. Keywords Artificial Neural Network, Multilayer Perceptron, RSRW, Severe Thunderstorm and Wind-shear
الوصف: Severe thunderstorm is a seasonal and mesoscale atmospheric event. The sudden increase in wind speed and the other weather features during this event have various destructive effects on the people. Correct forecasting with enough lead time is very important to minimize the damages occurring in day-to-day life. In this paper, artificial neural network technique has been applied to predict the severe thunderstorm. Multilayer Perceptron (MLP) has been applied on the weather parameters of moisture difference, adiabatic lapse rate and vertical wind shear which were recorded by the radiosonde-rawind (RSRW) in the early morning at 06.00 am local time. MLP classified and predicted „severe storm ‟ and „no storm‟ days in this work correctly nearly up to 70 % having around 12 hours lead time.
نوع الوثيقة: text
وصف الملف: application/pdf
اللغة: English
العلاقة: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.686.2494Test; http://research.ijcaonline.org/volume89/number16/pxc3894362.pdfTest
الإتاحة: http://research.ijcaonline.org/volume89/number16/pxc3894362.pdfTest
حقوق: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
رقم الانضمام: edsbas.F732531C
قاعدة البيانات: BASE