Predicting geological interfaces using stacking ensemble learning with multi-scale features
Understanding the variation of geological interfaces plays a crucial role in the analysis and
design of infrastructure systems. Generally, there are two classes of techniques for …
design of infrastructure systems. Generally, there are two classes of techniques for …
A novel data-driven optimization framework for unsupervised and multivariate early-warning threshold modification in risk assessment of deep excavations
Due to the great uncertainty and complexity in the underground environment, precious risk
perception in underground construction is a highly challenging problem. Excessive false …
perception in underground construction is a highly challenging problem. Excessive false …
A deep learning framework for predicting slab transverse crack using multivariate LSTM-FCN in continuous casting
M Geng, H Ma, J Wang, S Liu, J Li, Y Ai… - Expert Systems with …, 2025 - Elsevier
Accurate and timely predictions of transverse cracks in slabs are crucial for ensuring efficient
and high-quality production in continuous casting. However, the accumulation of substantial …
and high-quality production in continuous casting. However, the accumulation of substantial …
Enhanced resilience in smart grids: A neural network-based detection of data integrity attacks using improved war strategy optimization
Ensuring the resilience and security of Smart Grid (SG) infrastructure is critical for
sustainable energy management. This paper proposes a new probabilistic approach for …
sustainable energy management. This paper proposes a new probabilistic approach for …
Sparse regularized graph pooling network optimal sensor placement method for diesel engine vibration fault perception system
A Huang, Z Mao, F Liu, J Zhang, X Kong, Z Jiang - Measurement, 2025 - Elsevier
Vibration sensor network optimization increases monitoring effectiveness and reduces
sensor quantity and transmission burden. However, the traditional model-driven methods …
sensor quantity and transmission burden. However, the traditional model-driven methods …
A bi‐fidelity inverse analysis method for deep excavations considering three‐dimensional effects
Y Tao, S Pan, H Sun, Y Cai, G Zhang… - International Journal for …, 2024 - Wiley Online Library
Inverse analysis methods are commonly used in braced excavations for improved
deformation predictions. This paper proposes a bi‐fidelity ensemble randomized maximum …
deformation predictions. This paper proposes a bi‐fidelity ensemble randomized maximum …
Building a Bridge between Building Information Modeling and Digital Twins: Introducing Invariant Signatures of Architecture, Engineering, and Construction Objects
This chapter focuses on the discovery of invariant signatures of architecture, engineering,
and construction (AEC) objects, how it helps with Building Information Modeling (BIM) …
and construction (AEC) objects, how it helps with Building Information Modeling (BIM) …