Causality-based multi-model ensemble learning for safety assessment in metro tunnel construction
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DOI: 10.1016/j.ress.2023.109168
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- Wei, Pengfei & Zheng, Yu & Fu, Jiangfeng & Xu, Yuannan & Gao, Weikai, 2023. "An expected integrated error reduction function for accelerating Bayesian active learning of failure probability," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
- Ouyang, Min & Liu, Chuang & Wu, Shengyu, 2020. "Worst-case vulnerability assessment and mitigation model of urban utility tunnels," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
- Xu, Zizhen & Chopra, Shauhrat S., 2022. "Network-based Assessment of Metro Infrastructure with a Spatial–temporal Resilience Cycle Framework," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
- Nagulapati, Vijay Mohan & Lee, Hyunjun & Jung, DaWoon & Brigljevic, Boris & Choi, Yunseok & Lim, Hankwon, 2021. "Capacity estimation of batteries: Influence of training dataset size and diversity on data driven prognostic models," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
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Keywords
Data causality; Multi-model; Ensemble learning; Safety assessment; Metro tunnel construction (MTC);All these keywords.
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