Drought forecasting using feed-forward neural network

Please use this identifier to cite or link to this item: https://dspace.univ-ouargla.dz/jspui/handle/123456789/14180

Title:	Drought forecasting using feed-forward neural network
Authors:	Sarah, HELLASSA Doudja, SOUAG Salim, DJERBOUAI
Keywords:	Drought ARIMA SARIMA FFNN Forecasting
Issue Date:	13-Jun-2017
Series/Report no.:	2016;
Abstract:	Drought forecasting is a major component of a drought preparedness and mitigation plan. This study compares linear stochastic models (ARIMA/SARIMA) and Feed-forward neural network (FFNN) models for drought forecasting in the Algerois catchment in Algeria, using standardized precipitation index (SPI) as a drought quantifying parameter. The results obtained from two models are presented in this paper.
Description:	الملتقى الدولي الثاني حول: الموارد المائية'' تقييم و إقتصاد وحماية'' یومي الاثنین والثلاثاء 21 و22 دیسمبر 2016
URI:	http://dspace.univ-ouargla.dz/jspui/handle/123456789/14180
ISSN:	sa
Appears in Collections:	3. Faculté des sciences appliquées

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