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International Journal of Engineering، جلد ۲۷، شماره ۷، صفحات ۱۰۴۱-۱۰۵۰
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عنوان فارسی |
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چکیده فارسی مقاله |
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کلیدواژههای فارسی مقاله |
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عنوان انگلیسی |
A Novel Fuzzy Based Method for Heart Rate Variability Prediction |
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چکیده انگلیسی مقاله |
Abstract In this paper, a novel technique based on fuzzy method is presented for chaotic nonlinear time series prediction. Fuzzy approach with the gradient learning algorithm and methods constitutes the main components of this method. This learning process in this method is similar to conventional gradient descent learning process, except that the input patterns and parameters are stored in memory as a look-up table after upgrade. In the testing phase according to input patterns, the nearest neighbors and the weights corresponding to the test pattern, similar patterns are extracted from memory. Eventually by extracted weights and input pattern, prediction is performed. In order to validate the proposed method for predicting, the Mackey-Glass, Lorenz and biological Heart Rate Variability (HRV) time series is used. Finally, results of proposed method with the conventional methods of time-series prediction are also compared. The results demonstrate the capability of proposed method in chaotic time series prediction. |
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کلیدواژههای انگلیسی مقاله |
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نویسندگان مقاله |
Hossein Gholizade-Narm | Electrical and Robotic, University of Shahrood
Mohammad Reza Shafiee | Electrical, Shahrood
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نشانی اینترنتی |
http://www.ije.ir/article_72337_e18535183936b997270355f957764e49.pdf |
فایل مقاله |
اشکال در دسترسی به فایل - ./files/site1/rds_journals/409/article-409-2062688.pdf |
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زبان مقاله منتشر شده |
en |
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نوع مقاله منتشر شده |
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