Drilling Condition Identification Method for Imbalanced Datasets

Drilling Condition Identification Method for Imbalanced Datasets

To address the challenges posed by class imbalance and temporal dependency in drilling condition data and enhance the accuracy of condition identification, this study proposes an integrated method combining feature engineering, data resampling, and deep learning model optimization. Firstly, a featur...

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Bibliographic Details
Main Authors: Yibing Yu, Huilin Yang, Fengjia Peng, Xi Wang
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
drilling condition
imbalanced data
feature selection
bidirectional long short-term memory network
gated recurrent unit
Online Access:https://www.mdpi.com/2076-3417/15/6/3362
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