Differentiating between regular and abnormal noises in machine-generated sounds is a crucial but difficult problem.For accurate audio signal classification,suitable and efficient techniques are needed,particularly mac...Differentiating between regular and abnormal noises in machine-generated sounds is a crucial but difficult problem.For accurate audio signal classification,suitable and efficient techniques are needed,particularly machine learning approaches for automated classification.Due to the dynamic and diverse representative characteristics of audio data,the probability of achieving high classification accuracy is relatively low and requires further research efforts.This study proposes an ensemble model based on the LeNet and hierarchical attention mechanism(HAM)models with MFCC features to enhance the models’capacity to handle bias.Additionally,CNNs,bidirectional LSTM(BiLSTM),CRNN,LSTM,capsule network model(CNM),attention mechanism(AM),gated recurrent unit(GRU),ResNet,EfficientNet,and HAM models are implemented for performance comparison.Experiments involving the DCASE2020 dataset reveal that the proposed approach works better than the others,achieving an impressive 99.13%accuracy and 99.56%k-fold cross-validation accuracy.Comparison with state-of-the-art studies further validates this performance.The study’s findings highlight the potential of the proposed approach for accurate fault detection in vehicles,particularly involving the use of acoustic data.展开更多
The degradation and nonlinear interactions of a two-breather solution of the Mel’nikov equation are analyzed.By modulating the phase shift and limit method,we prove that in different regions near the non-singular bou...The degradation and nonlinear interactions of a two-breather solution of the Mel’nikov equation are analyzed.By modulating the phase shift and limit method,we prove that in different regions near the non-singular boundaries,there are four kinds of solutions with repulsive interaction or attractive interaction in addition to the two-breather solution.They are the interaction solution between soliton and breather,the two-soliton solution,and the two-breather solution with small amplitude,which all exhibit repulsive interactions;and the two-breather solution with small amplitude,which exhibits attractive interaction.Interestingly,a new breather acts as a messenger to transfer energy during the interaction between two breather solutions with small amplitude.展开更多
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R746),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia。
文摘Differentiating between regular and abnormal noises in machine-generated sounds is a crucial but difficult problem.For accurate audio signal classification,suitable and efficient techniques are needed,particularly machine learning approaches for automated classification.Due to the dynamic and diverse representative characteristics of audio data,the probability of achieving high classification accuracy is relatively low and requires further research efforts.This study proposes an ensemble model based on the LeNet and hierarchical attention mechanism(HAM)models with MFCC features to enhance the models’capacity to handle bias.Additionally,CNNs,bidirectional LSTM(BiLSTM),CRNN,LSTM,capsule network model(CNM),attention mechanism(AM),gated recurrent unit(GRU),ResNet,EfficientNet,and HAM models are implemented for performance comparison.Experiments involving the DCASE2020 dataset reveal that the proposed approach works better than the others,achieving an impressive 99.13%accuracy and 99.56%k-fold cross-validation accuracy.Comparison with state-of-the-art studies further validates this performance.The study’s findings highlight the potential of the proposed approach for accurate fault detection in vehicles,particularly involving the use of acoustic data.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.52171251 and U21062251)Program of Science and Technology Innovation of Dalian(Grant No.2022JJ12GX036).
文摘The degradation and nonlinear interactions of a two-breather solution of the Mel’nikov equation are analyzed.By modulating the phase shift and limit method,we prove that in different regions near the non-singular boundaries,there are four kinds of solutions with repulsive interaction or attractive interaction in addition to the two-breather solution.They are the interaction solution between soliton and breather,the two-soliton solution,and the two-breather solution with small amplitude,which all exhibit repulsive interactions;and the two-breather solution with small amplitude,which exhibits attractive interaction.Interestingly,a new breather acts as a messenger to transfer energy during the interaction between two breather solutions with small amplitude.
