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Development of a novel approach for strain demand prediction of pipes at fault crossings on the basis of multi-layer neural network driven by strain data

Xiaoben Liu, Qian Zheng, Kai Wu, Yue Yang, Ziqi Zhao, Hong Zhang

2020Engineering Structures29 citationsDOIOpen Access PDF

Topics & Concepts

Pipeline transportArtificial neural networkPython (programming language)Structural engineeringFinite element methodMATLABEngineeringPipeline (software)Fault (geology)Computer scienceMechanical engineeringGeologyArtificial intelligenceSeismologyOperating systemGeotechnical Engineering and Underground StructuresStructural Integrity and Reliability AnalysisGeophysical Methods and Applications
Development of a novel approach for strain demand prediction of pipes at fault crossings on the basis of multi-layer neural network driven by strain data | Litcius