A Case Study to Predict Structural Health of a Gasoline Pipeline Using ANN and GPR Approaches
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-1939-8_47
Reference20 articles.
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1. Fast dynamic prediction of consequences of heavy gas leakage accidents based on machine learning;Frontiers in Environmental Science;2024-07-23
2. A novel neural network-based framework to estimate oil and gas pipelines life with missing input parameters;Scientific Reports;2024-02-24
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