Research on the Application of Data Mining Algorithm in the Detection of Gas Pipeline Outside
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-4121-2_31
Reference10 articles.
1. Alexander, J., et al.: Laboratory and field experiment validations on the use of hydraulic transients for estimating buried water pipeline deterioration. Struct. Health Monit. Int. J. 22(2), 814–831 (2023)
2. Babaeian, A., et al.: Risk-based inspection (RBI) of a gas pressure reduction station. J. Loss Prev. Process Ind. 84, 105100 (2023)
3. El-Abbasy, M.S., et al.: Optimized maintenance plan for oil and gas pipelines. Can. J. Civ. Eng. 49(7), 1151–1162 (2022)
4. Parlak, B.O., Yavasoglu, H.A.: A comprehensive analysis of in-line inspection tools and technologies for steel oil and gas pipelines. Sustainability 15(3), 2783 (2023)
5. Stodt, F., et al.: Blockchain secured dynamic machine learning pipeline for manufacturing. Appl. Sci. 13(2), 782 (2023)
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