Control chart pattern classification using Fourier descriptors and neural networks
This paper presents the method of Fourier descriptors and neural networks developed for control chart pattern analysis. The pattern analysis is important to achieve appropriate control and to produce high quality products. This paper also investigates the use of features extracted from Fourier descr...
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th-mahidol.116512018-05-03T15:10:34Z Control chart pattern classification using Fourier descriptors and neural networks Pisit Phokharatkul Supachai Phaiboon Mahidol University Business, Management and Accounting Computer Science Economics, Econometrics and Finance This paper presents the method of Fourier descriptors and neural networks developed for control chart pattern analysis. The pattern analysis is important to achieve appropriate control and to produce high quality products. This paper also investigates the use of features extracted from Fourier descriptors as the Fourier coefficient components. The Fourier coefficients used to train the neural networks for classifying patterns. Thus, the networks were able to identify the classes. This research concluded the extracted features to improve the performance of the number of Fourier coefficients for neural network training. Experimental results and comparisons based on simulated and unknown data show that the proposed approach performs better than the symbol-sequence histogram with neural network approach. © 2011 IEEE. 2018-05-03T08:05:38Z 2018-05-03T08:05:38Z 2011-10-03 Conference Paper 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce, AIMSEC 2011 - Proceedings. (2011), 4587-4590 10.1109/AIMSEC.2011.6011169 2-s2.0-80053246755 https://repository.li.mahidol.ac.th/handle/123456789/11651 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=80053246755&origin=inward |
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Business, Management and Accounting Computer Science Economics, Econometrics and Finance Pisit Phokharatkul Supachai Phaiboon Control chart pattern classification using Fourier descriptors and neural networks |
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This paper presents the method of Fourier descriptors and neural networks developed for control chart pattern analysis. The pattern analysis is important to achieve appropriate control and to produce high quality products. This paper also investigates the use of features extracted from Fourier descriptors as the Fourier coefficient components. The Fourier coefficients used to train the neural networks for classifying patterns. Thus, the networks were able to identify the classes. This research concluded the extracted features to improve the performance of the number of Fourier coefficients for neural network training. Experimental results and comparisons based on simulated and unknown data show that the proposed approach performs better than the symbol-sequence histogram with neural network approach. © 2011 IEEE. |
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Mahidol University |
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Mahidol University Pisit Phokharatkul Supachai Phaiboon |
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Conference or Workshop Item |
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Pisit Phokharatkul Supachai Phaiboon |
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Pisit Phokharatkul |
title |
Control chart pattern classification using Fourier descriptors and neural networks |
title_short |
Control chart pattern classification using Fourier descriptors and neural networks |
title_full |
Control chart pattern classification using Fourier descriptors and neural networks |
title_fullStr |
Control chart pattern classification using Fourier descriptors and neural networks |
title_full_unstemmed |
Control chart pattern classification using Fourier descriptors and neural networks |
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control chart pattern classification using fourier descriptors and neural networks |
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2018 |
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https://repository.li.mahidol.ac.th/handle/123456789/11651 |
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1763491180761317376 |