Arrhythmia classification method based on genetic algorithm optimization of C-LSTM model
A GC-LSTM model is proposed based on the characteristics of global optimization of genetic algorithm.The model automatically and iteratively searches the optimal hyper-parameter configuration of the C-LSTM model through the genetic algorithm of a specific genetic strategy,and it is configured using the genetic iteration results and validated on the MIT-BIH arrhythmia database according to the classification criteria of the Association for the Advancement of Medical Instrumentation.The testing shows that the classification accuracy,sensitivity,accuracy and F1 value of GC-LSTM model are 99.37%,95.62%,95.17%and 95.39%,respectively,higher than those of the manually established model,and it is also advantageous over the existing mainstream methods.Experimental results demonstrate that the proposed method can achieve better classification performance while avoiding a large number of experimental parameters.
万方数据
维普
