Using Fuzzy Feed-Forward Neural Network for Linguistic Processing
Fuzzy sets have been implemented efficiently to manage unclear data, language terms, and vague notions. Recently, considerable work has been dedicated to merging neural-network techniques with fuzzy sets. In this study, present the structure of a fuzzy feed-forward neural network (FFFNN) with a tra...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
College of science, university of Diyala
2023-04-01
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| Series: | Academic Science Journal |
| Online Access: | https://acadscij.uodiyala.edu.iq/index.php/Home/article/view/115 |
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| Summary: | Fuzzy sets have been implemented efficiently to manage unclear data, language terms, and
vague notions. Recently, considerable work has been dedicated to merging neural-network
techniques with fuzzy sets. In this study, present the structure of a fuzzy feed-forward neural
network (FFFNN) with a trapezoidal fuzzy set. In addition to handling real input vectors, it is
also capable of handling fuzzy input vectors. Generally, the output of a FNN is a fuzzy vector.
According to the extension principle of Zadeh, each unit of a FNN has an input-output
relationship. To determine the costs associated with fuzzy calculations and fuzzy objectives,
developed a cost function. At that point, created a learning algorithm from the cost capacity to
align the four variables of each trapezoidal fuzzy weight. In conclusion, demonstrate our
methodology using numerical models.
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| ISSN: | 2958-4612 2959-5568 |