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(searched for: doi:10.11591/ijece.v11i3.pp2315-2326)
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Michael Lahzi Gaid, , ,
Proceedings of the 2nd International Conference on Data Engineering and Communication Technology pp 742-753; https://doi.org/10.1007/978-3-030-76346-6_66

Abstract:
The concept of using two neural networks to translate one Sequence to another sequence presented by google in 2014 has led to a revolutionary result of translation between the input sequence as source language and the output sequence as the target language. It overcomes the weakness of previous translation methods. On the other hand, C#.Net programming language becomes a widely-used programming language, as it is similar to the English language. Besides, it has a strong memory backup. However, it doesn’t support other scientific functions like the sigmoid and tahn functions. This paper proposes an implementation of Sequence to Sequence algorithm using C#, and resolving the inability of C# in calculating the activation function by polynomial simplifying the sigmoid and tahn functions. Moreover, creating a small training and testing dataset using United Nation Arabic and English Letters from the official UN website as an approved translation source.
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