Deep learning of lithium-ion battery SOH using the DeTransformer model learns the aging characteristics of the battery and then makes predictions about the battery SOH in order to monitor the health of batteries in electric vehicles.
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Question about the Consistency of DeTransformer.py Results #2
Thank you for your sharing. I am wondering if the results of the DeTransformer.py code file remain the same with each run, or do they vary? I noticed in your visualization that there are paths to Transformer__num, which suggests to me that the results might differ with each run and that you trained it multiple times, correct? Thank you!
Thank you for your sharing. I am wondering if the results of the DeTransformer.py code file remain the same with each run, or do they vary? I noticed in your visualization that there are paths to Transformer__num, which suggests to me that the results might differ with each run and that you trained it multiple times, correct? Thank you!