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Published in 2020 at "Ocean Engineering"
DOI: 10.1016/j.oceaneng.2020.107263
Abstract: Abstract This study proposes a hybrid surrogate modelling approach with the integration of deep learning algorithm long short-term memory (LSTM) to identify the mechanical responses of caisson foundations in marine soils. The LSTM based surrogate…
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Keywords:
modelling approach;
caisson foundations;
lstm based;
surrogate modelling ... See more keywords
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Published in 2019 at "Cogent Engineering"
DOI: 10.1080/23311916.2019.1631009
Abstract: Abstract Production from thin oil rim reservoirs can be very challenging due to the thin spread of the oil resources, complicated mechanism of production and fluid contact movement. Typically, the recovery from these types of…
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Keywords:
production;
modelling approach;
surrogate modelling;
oil ... See more keywords
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Published in 2022 at "PLoS ONE"
DOI: 10.1371/journal.pone.0263150
Abstract: In this proof-of-concept work, we evaluate the performance of multiple machine-learning methods as surrogate models for use in the analysis of agent-based models (ABMs). Analysing agent-based modelling outputs can be challenging, as the relationships between…
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Keywords:
surrogate modelling;
agent based;
machine learning;
model ... See more keywords
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Published in 2025 at "Applied Sciences"
DOI: 10.3390/app15158740
Abstract: Surrogate modelling is increasingly used in engineering to improve computational efficiency in complex simulations. However, traditional data-driven surrogate models often face limitations in generalizability, physical consistency, and extrapolation—issues that are especially critical in safety-sensitive fields…
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Keywords:
fire safety;
engineering;
physics;
surrogate modelling ... See more keywords