Feature dimensionality reduction for recognition of Persian handwritten letters using a combination of quantum genetic algorithm and neural network
Curse of dimensionality is one of the biggest challenges in classification problems. High dimensionality of problem increases classification rate and brings about classification error. Selecting an effective subset of features is an important point in analyzing correlation rate in classification iss...
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| Format: | Article |
| Language: | English |
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OICC Press
2024-02-01
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| Series: | Majlesi Journal of Electrical Engineering |
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| Online Access: | https://oiccpress.com/mjee/article/view/4779 |
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| author | Mohammad Javad Aranian Moein Sarvaghad-Moghaddam Monireh Houshmand |
| author_facet | Mohammad Javad Aranian Moein Sarvaghad-Moghaddam Monireh Houshmand |
| author_sort | Mohammad Javad Aranian |
| collection | DOAJ |
| description | Curse of dimensionality is one of the biggest challenges in classification problems. High dimensionality of problem increases classification rate and brings about classification error. Selecting an effective subset of features is an important point in analyzing correlation rate in classification issues. The main purpose of this paper is enhancing characters recognition and classification, creating quick and low-cost classes, and eventually recognizing Persian handwritten characters more accurately and faster. In this paper, to reduce feature dimensionality of datasets a hybrid approach using artificial neural network, genetic algorithm and quantum genetic algorithm is proposed that can be used to distinguish Persian handwritten letters. Implementation results show that proposed algorithms are able to reduce number of features by 19% to 49%. They also show that recognition and classification accuracy of resulted subset of features has risen, by 7/31%, comparing to primitive dataset. |
| format | Article |
| id | doaj-art-d4de9ffdec0d4e51804c29ca71f968a8 |
| institution | OA Journals |
| issn | 2345-377X 2345-3796 |
| language | English |
| publishDate | 2024-02-01 |
| publisher | OICC Press |
| record_format | Article |
| series | Majlesi Journal of Electrical Engineering |
| spelling | doaj-art-d4de9ffdec0d4e51804c29ca71f968a82025-08-20T02:15:54ZengOICC PressMajlesi Journal of Electrical Engineering2345-377X2345-37962024-02-01112Feature dimensionality reduction for recognition of Persian handwritten letters using a combination of quantum genetic algorithm and neural networkMohammad Javad Aranian0Moein Sarvaghad-Moghaddam1Monireh Houshmand2Imam Reza International UniversitySemnan UniversityImam Reza International UniversityCurse of dimensionality is one of the biggest challenges in classification problems. High dimensionality of problem increases classification rate and brings about classification error. Selecting an effective subset of features is an important point in analyzing correlation rate in classification issues. The main purpose of this paper is enhancing characters recognition and classification, creating quick and low-cost classes, and eventually recognizing Persian handwritten characters more accurately and faster. In this paper, to reduce feature dimensionality of datasets a hybrid approach using artificial neural network, genetic algorithm and quantum genetic algorithm is proposed that can be used to distinguish Persian handwritten letters. Implementation results show that proposed algorithms are able to reduce number of features by 19% to 49%. They also show that recognition and classification accuracy of resulted subset of features has risen, by 7/31%, comparing to primitive dataset.https://oiccpress.com/mjee/article/view/4779Dimensionality reduction of featuresGenetic Algorithm (GA)quantum genetic algorithm (QGA). Neural Networksrecognition of Persian handwritten letters |
| spellingShingle | Mohammad Javad Aranian Moein Sarvaghad-Moghaddam Monireh Houshmand Feature dimensionality reduction for recognition of Persian handwritten letters using a combination of quantum genetic algorithm and neural network Majlesi Journal of Electrical Engineering Dimensionality reduction of features Genetic Algorithm (GA) quantum genetic algorithm (QGA). Neural Networks recognition of Persian handwritten letters |
| title | Feature dimensionality reduction for recognition of Persian handwritten letters using a combination of quantum genetic algorithm and neural network |
| title_full | Feature dimensionality reduction for recognition of Persian handwritten letters using a combination of quantum genetic algorithm and neural network |
| title_fullStr | Feature dimensionality reduction for recognition of Persian handwritten letters using a combination of quantum genetic algorithm and neural network |
| title_full_unstemmed | Feature dimensionality reduction for recognition of Persian handwritten letters using a combination of quantum genetic algorithm and neural network |
| title_short | Feature dimensionality reduction for recognition of Persian handwritten letters using a combination of quantum genetic algorithm and neural network |
| title_sort | feature dimensionality reduction for recognition of persian handwritten letters using a combination of quantum genetic algorithm and neural network |
| topic | Dimensionality reduction of features Genetic Algorithm (GA) quantum genetic algorithm (QGA). Neural Networks recognition of Persian handwritten letters |
| url | https://oiccpress.com/mjee/article/view/4779 |
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