Reinforcement Learning Based Artificial Immune Classifier
One of the widely used methods for classification that is a decision-making process is artificial immune systems. Artificial immune systems based on natural immunity system can be successfully applied for classification, optimization, recognition, and learning in real-world problems. In this study,...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2013/581846 |
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| _version_ | 1841524444479094784 |
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| author | Mehmet Karakose |
| author_facet | Mehmet Karakose |
| author_sort | Mehmet Karakose |
| collection | DOAJ |
| description | One of the widely used methods for classification that is a decision-making process is artificial immune systems. Artificial immune systems based on natural immunity system can be successfully applied for classification, optimization, recognition, and learning in real-world problems. In this study, a reinforcement learning based artificial immune classifier is proposed as a new approach. This approach uses reinforcement learning to find better antibody with immune operators. The proposed new approach has many contributions according to other methods in the literature such as effectiveness, less memory cell, high accuracy, speed, and data adaptability. The performance of the proposed approach is demonstrated by simulation and experimental results using real data in Matlab and FPGA. Some benchmark data and remote image data are used for experimental results. The comparative results with supervised/unsupervised based artificial immune system, negative selection classifier, and resource limited artificial immune classifier are given to demonstrate the effectiveness of the proposed new method. |
| format | Article |
| id | doaj-art-37d394d832f04f9caf6e805e4602bb6e |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-37d394d832f04f9caf6e805e4602bb6e2025-02-03T05:53:12ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/581846581846Reinforcement Learning Based Artificial Immune ClassifierMehmet Karakose0Computer Engineering Department, Firat University, Elazig, TurkeyOne of the widely used methods for classification that is a decision-making process is artificial immune systems. Artificial immune systems based on natural immunity system can be successfully applied for classification, optimization, recognition, and learning in real-world problems. In this study, a reinforcement learning based artificial immune classifier is proposed as a new approach. This approach uses reinforcement learning to find better antibody with immune operators. The proposed new approach has many contributions according to other methods in the literature such as effectiveness, less memory cell, high accuracy, speed, and data adaptability. The performance of the proposed approach is demonstrated by simulation and experimental results using real data in Matlab and FPGA. Some benchmark data and remote image data are used for experimental results. The comparative results with supervised/unsupervised based artificial immune system, negative selection classifier, and resource limited artificial immune classifier are given to demonstrate the effectiveness of the proposed new method.http://dx.doi.org/10.1155/2013/581846 |
| spellingShingle | Mehmet Karakose Reinforcement Learning Based Artificial Immune Classifier The Scientific World Journal |
| title | Reinforcement Learning Based Artificial Immune Classifier |
| title_full | Reinforcement Learning Based Artificial Immune Classifier |
| title_fullStr | Reinforcement Learning Based Artificial Immune Classifier |
| title_full_unstemmed | Reinforcement Learning Based Artificial Immune Classifier |
| title_short | Reinforcement Learning Based Artificial Immune Classifier |
| title_sort | reinforcement learning based artificial immune classifier |
| url | http://dx.doi.org/10.1155/2013/581846 |
| work_keys_str_mv | AT mehmetkarakose reinforcementlearningbasedartificialimmuneclassifier |