Integrated applications of building information modeling and artificial intelligence techniques in the AEC/FM industry
Informatization and automatization are considered mainstream trends in the future
architecture-engineering-construction/facility management (AEC/FM) industry. Building …
architecture-engineering-construction/facility management (AEC/FM) industry. Building …
A novel approach to uncertainty quantification in groundwater table modeling by automated predictive deep learning
Uncertainty quantification (UQ) is an important benchmark to assess the performance of
artificial intelligence (AI) and particularly deep learning ensembled-based models. However …
artificial intelligence (AI) and particularly deep learning ensembled-based models. However …
Fire detection in video surveillances using convolutional neural networks and wavelet transform
Fire is one of the most frequent and common emergencies threatening public safety and
social development. Recently, intelligent fire detection technologies represented by …
social development. Recently, intelligent fire detection technologies represented by …
Centrifuge modeling of multi-row stabilizing piles reinforced reservoir landslide with different row spacings
C Zhang, Y Yin, H Yan, S Zhu, B Li, X Hou, Y Yang - Landslides, 2023 - Springer
The multi-row stabilizing piles have been applied in the stabilization of large-scale reservoir
landslides in recent years. However, the mechanical behavior and deformation …
landslides in recent years. However, the mechanical behavior and deformation …
Battling COVID-19 using machine learning: A review
Abstract Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) known as
Coronavirus surfaced in late 2019. It turned out to be a life-threatening disease and is …
Coronavirus surfaced in late 2019. It turned out to be a life-threatening disease and is …
[HTML][HTML] A visualized hybrid intelligent model to delineate Swedish fine-grained soil layers using clay sensitivity
In the current paper, a hybrid model was developed to generate 3D delineated soil horizons
using clay sensitivity (S t) with 1 m depth intervals in a landslide prone area in the southwest …
using clay sensitivity (S t) with 1 m depth intervals in a landslide prone area in the southwest …
Non-intrusive surrogate modeling for parametrized time-dependent partial differential equations using convolutional autoencoders
This paper presents a novel non-intrusive surrogate modeling scheme based on deep
learning for predictive modeling of complex systems, described by parametrized time …
learning for predictive modeling of complex systems, described by parametrized time …
Exploring a landslide inventory created by automated web data mining: the case of Italy
Nowadays, several systems to set up landslide inventories exist although they rarely rely on
automated or real-time updates. Mass media can provide reliable info about natural hazard …
automated or real-time updates. Mass media can provide reliable info about natural hazard …
Identification and classification for multiple cyber attacks in power grids based on the deep capsule CNN
Cyber-attacks have become one of the main threats to the security, reliability, and economic
operation of power systems. Detection and classification of multiple cyber-attacks pose …
operation of power systems. Detection and classification of multiple cyber-attacks pose …
A CNN pruning approach using constrained binary particle swarm optimization with a reduced search space for image classification
Deep convolutional neural networks (CNNs) have exhibited exceptional performance in a
range of computer vision tasks. However, these deep CNNs typically demand significant …
range of computer vision tasks. However, these deep CNNs typically demand significant …