Using the Backpropagation Algorithm to Distinguish Arabic Alphabet


  • Samyia Khalid Hasan College of Administration & Economics, Salahaddin University-Erbil



networks neural artificial, back propagation algorithm, weights, input and output.


In this research, a study of the Arabic alphabet used a multi-layered neural network, which is the backpropagation error. Using the algorithm through the Losing activation function to train the network. The hidden numbers of nodes are 10, the number of cycles is 500, and the error is 0.001, using the Matlab R2013a program. The aim of the study It is the use of the network algorithm to recognize the characters, by training the network to recognize the characters in two cases. The first case is inputting the image of the letter into the grid and the second case is identifying the letter that represents the letter drawn in the image. And it was reached that the algorithm used for the network of nervousness to recognize the Arabic alphabet and then show it correctly.


المصادر العربية

- أمين بك، عزه. (2004) استخدام الشبكات العصبية لتوقع الجدول الزمني للسلاسل. رسالة ماجستير ، كلية علوم الحاسوب والرياضيات ، جامعة الموصل.

- محمد صافي، غادة. (2011) آليات التعميم واتصال الذكي للنماذج العصبية الاصطناعية بدون مشرف من أجل معالجة البيانات الوثائقية. أطروحة دكتوراه في الرياضيات، قسم الإحصاء، كلية العلوم، حلب، الجامعة السوريا.

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How to Cite

Hasan, S. K. . (2024). Using the Backpropagation Algorithm to Distinguish Arabic Alphabet. Zanco Journal of Human Sciences, 28(1), 86–94.