TY - JOUR ID - 72337 TI - A Novel Fuzzy Based Method for Heart Rate Variability Prediction JO - International Journal of Engineering JA - IJE LA - en SN - 1025-2495 AU - Gholizade-Narm, Hossein AU - Shafiee, Mohammad Reza AD - Electrical and Robotic, University of Shahrood AD - Electrical, Shahrood Y1 - 2014 PY - 2014 VL - 27 IS - 7 SP - 1041 EP - 1050 KW - Fuzzy approach KW - chaos KW - Nearest Neighbor KW - heart rate variability KW - prediction DO - N2 - 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. UR - https://www.ije.ir/article_72337.html L1 - https://www.ije.ir/article_72337_e18535183936b997270355f957764e49.pdf ER -