Processing time series data using the sliding window method, where t represents the label of the time series segment.

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Bibliographic Details
Main Author:	Changsheng Li (278602) (author)
Other Authors:	Xinsong Zhang (21212409) (author)
Published:	2025
Subjects:	Microbiology Biological Sciences not elsewhere classified Information Systems not elsewhere classified term memory autoencoder handling large datasets complex mechanical properties biaxial compression using recurrent neural network predicting 10 sets encoder extracts features ae approach uses div >< p >< sup ae network valuable reference true values target sequence study provides strain curves strain behavior special samples significantly advanced rock materials rmse </ results indicate r </ paper proposes mse </ mae </ lstm network long short input data evaluation metrics determination (< deep learning
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Processing time series data using the sliding window method, where <i>t</i> represents the label of the time series segment.