Using the Backpropagation Algorithm to Distinguish Arabic Alphabet
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 t...
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| Format: | Article |
| Language: | Arabic |
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Salahaddin University-Erbil
2024-02-01
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| Series: | Zanco Journal of Humanity Sciences |
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| Online Access: | https://zancojournal.su.edu.krd/index.php/JAHS/article/view/1463 |
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| author | Samyia Khalid Hasan |
| author_facet | Samyia Khalid Hasan |
| author_sort | Samyia Khalid Hasan |
| collection | DOAJ |
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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.
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| format | Article |
| id | doaj-art-dbc95809d1f146fa98e2df17a5e4a7e2 |
| institution | Kabale University |
| issn | 2412-396X |
| language | Arabic |
| publishDate | 2024-02-01 |
| publisher | Salahaddin University-Erbil |
| record_format | Article |
| series | Zanco Journal of Humanity Sciences |
| spelling | doaj-art-dbc95809d1f146fa98e2df17a5e4a7e22025-08-20T03:43:41ZaraSalahaddin University-ErbilZanco Journal of Humanity Sciences2412-396X2024-02-0128110.21271/zjhs.28.1.6Using the Backpropagation Algorithm to Distinguish Arabic AlphabetSamyia Khalid Hasan0 College of Administration & Economics, Salahaddin University-Erbil 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. https://zancojournal.su.edu.krd/index.php/JAHS/article/view/1463networks neural artificial, back propagation algorithm, weights, input and output. |
| spellingShingle | Samyia Khalid Hasan Using the Backpropagation Algorithm to Distinguish Arabic Alphabet Zanco Journal of Humanity Sciences networks neural artificial, back propagation algorithm, weights, input and output. |
| title | Using the Backpropagation Algorithm to Distinguish Arabic Alphabet |
| title_full | Using the Backpropagation Algorithm to Distinguish Arabic Alphabet |
| title_fullStr | Using the Backpropagation Algorithm to Distinguish Arabic Alphabet |
| title_full_unstemmed | Using the Backpropagation Algorithm to Distinguish Arabic Alphabet |
| title_short | Using the Backpropagation Algorithm to Distinguish Arabic Alphabet |
| title_sort | using the backpropagation algorithm to distinguish arabic alphabet |
| topic | networks neural artificial, back propagation algorithm, weights, input and output. |
| url | https://zancojournal.su.edu.krd/index.php/JAHS/article/view/1463 |
| work_keys_str_mv | AT samyiakhalidhasan usingthebackpropagationalgorithmtodistinguisharabicalphabet |