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- W3113149095 abstract "Remaining useful life (RUL) prediction is a promising method for proton exchange membrane fuel cells (PEMFC) to save costs and expand applications. This paper proposes a model based on wavelet transform and long-short-term memory (LSTM), which uses a combination of neural networks and wavelet transform. First, the pre-processed voltage sequence of PEMFC data is wavelet decomposed, and LSTM prediction is performed on the decomposed sub-waveforms respectively, and the prediction result is wavelet reconstructed for voltage prediction. The results show that compared with the voltage prediction method using SVM, LSTM and BiLSTM, Wavelet-LSTM can perform more accurate prediction under different load conditions." @default.
- W3113149095 created "2020-12-21" @default.
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- W3113149095 date "2020-11-20" @default.
- W3113149095 modified "2023-10-14" @default.
- W3113149095 title "Prediction of Remaining Useful Life of Proton Exchange Membrane Fuel Cell based on Wavelet-LSTM" @default.
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- W3113149095 doi "https://doi.org/10.1109/ddcls49620.2020.9275255" @default.
- W3113149095 hasPublicationYear "2020" @default.
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