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Hybrid System for Cardiac Arrhythmia Classification with Fuzzy K-Nearest Neighbors and Neural Networks Combined by a Fuzzy Inference System.

, , and . Soft Computing for Recognition Based on Biometrics, volume 312 of Studies in Computational Intelligence, Springer, (2010)

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Hybrid Model Based on Neural Networks and Fuzzy Logic for 2-Lead Cardiac Arrhythmia Classification., , and . Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine, volume 827 of Studies in Computational Intelligence, Springer, (2020)Toward Improving the Fuzzy KNN Algorithm Based on Takagi-Sugeno Fuzzy Inference System., , and . NAFIPS, volume 1337 of Advances in Intelligent Systems and Computing, page 237-252. Springer, (2020)A new variant of Fuzzy K-Nearest Neighbor using Interval Type-2 Fuzzy Logic., , and . FUZZ-IEEE, page 1-7. IEEE, (2018)Hybrid model based on neural networks, type-1 and type-2 fuzzy systems for 2-lead cardiac arrhythmia classification., , and . Expert Syst. Appl., (2019)Hybrid System for Cardiac Arrhythmia Classification with Fuzzy K-Nearest Neighbors and Neural Networks Combined by a Fuzzy Inference System., , and . Soft Computing for Recognition Based on Biometrics, volume 312 of Studies in Computational Intelligence, Springer, (2010)A Modular Neural Network Approach for Cardiac Arrhythmia Classification., , and . Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms, volume 862 of Studies in Computational Intelligence, Springer, (2020)Hybrid intelligent system for cardiac arrhythmia classification with Fuzzy K-Nearest Neighbors and neural networks combined with a fuzzy system., , , and . Expert Syst. Appl., 39 (3): 2947-2955 (2012)Structure adaptation of stochastic neural nets using learning automata technique., and . Int. J. Systems Science, 29 (2): 139-148 (1998)Acceleration Output Prediction of Buildings Using a Polynomial Artificial Neural Network., and . Hybrid Intelligent Systems, volume 208 of Studies in Fuzziness and Soft Computing, (2007)Hybrid system for cardiac arrhythmia classification with fuzzy k-nearest neighbors and Multi Layer Perceptrons combined by a fuzzy inference system., , and . IJCNN, page 1-6. IEEE, (2010)