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The source code of paper: Trend attention fully convolutional network for remaining useful life estimation in the turbofan engine PHM of CMAPSS dataset. Signal selection, Attention mechanism, and Interpretability of deep learning are explored.

Python 100.00%
attention-mechanism cmapss fcn interpretability keras phm remaining-useful-life-prediction tensorflow

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ress-paper-2022.09-remaining-useful-life-prediction-by-tafcn's Issues

This CODE have a bug

interpretability_analysis.py
ValueError: Found unexpected instance while processing input tensors for keras functional model. Expecting KerasTensor which is from tf.keras.Input() or output from keras layer call(). Got: 0

How to solve this BUG?
I tried a lot of things,but I don't solved this BUG

How to calculate lossb ?

In your paper you said :
image
and x was an independent variable
But in you sharing code:
image
The lossb was only related to the ytrue label
Did I misunderstand? What exactly does x mean?

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