The phenomenon of cracking in cement concretes and reinforced concrete structures: the mechanism of cracks formation, causes of their initiation, types and places of …
GL Golewski - Buildings, 2023 - mdpi.com
Cracks and cavities belong to two basic forms of damage to the concrete structure, which
may reduce the load-bearing capacity and tightness of the structure and lead to failures and …
may reduce the load-bearing capacity and tightness of the structure and lead to failures and …
Machine learning techniques for structural health monitoring of heritage buildings: A state-of-the-art review and case studies
M Mishra - Journal of Cultural Heritage, 2021 - Elsevier
This paper performed a systematic review of the various machine learning (ML) techniques
applied to assess the health condition of heritage buildings. More robust predictive models …
applied to assess the health condition of heritage buildings. More robust predictive models …
Logistic regression for machine learning in process tomography
The main goal of the research presented in this paper was to develop a refined machine
learning algorithm for industrial tomography applications. The article presents algorithms …
learning algorithm for industrial tomography applications. The article presents algorithms …
[PDF][PDF] Maintenance of industrial reactors supported by deep learning driven ultrasound tomography
Monitoring of industrial processes is an important element ensuring the proper maintenance
of equipment and high level of processes reliability. The presented research concerns the …
of equipment and high level of processes reliability. The presented research concerns the …
Estimating punching shear capacity of steel fibre reinforced concrete slabs using sequential piecewise multiple linear regression and artificial neural network
ND Hoang - Measurement, 2019 - Elsevier
Estimating punching shear capacity is an important task in the design of steel fibre
reinforced concrete (SFRC) flat slabs. The accuracy of commonly employed empirical …
reinforced concrete (SFRC) flat slabs. The accuracy of commonly employed empirical …
Evaluation of the strength of slab-column connections with FRPs using machine learning algorithms
Slab-column connections with FRPs fail suddenly without warning. Machine learning (ML)
models can model the behavior with high precision and reliability. Nineteen ML algorithms …
models can model the behavior with high precision and reliability. Nineteen ML algorithms …
Random forest algorithm and support vector machine for nondestructive assessment of mass moisture content of brick walls in historic buildings
The article presents the results of experimental research and numerical analyses, and also
shows the usefulness of the random forest algorithm and the support vector machine for the …
shows the usefulness of the random forest algorithm and the support vector machine for the …
Modelling the influence of waste rubber on compressive strength of concrete by artificial neural networks
One of the major causes of ecological and environmental problems comes from the
enormous number of discarded waste tires, which is directly connected to the exponential …
enormous number of discarded waste tires, which is directly connected to the exponential …
[HTML][HTML] Machine learning models applied to moisture assessment in building materials
Moisture-related defects hinder long-term building durability and must be prevented. Non-
destructive techniques that measure the surface temperature of building materials have …
destructive techniques that measure the surface temperature of building materials have …
Predicting Rainfall‐Induced Soil Erosion Based on a Hybridization of Adaptive Differential Evolution and Support Vector Machine Classification
Soil erosion induced by rainfall is a critical problem in many regions in the world, particularly
in tropical areas where the annual rainfall amount often exceeds 2000 mm. Predicting soil …
in tropical areas where the annual rainfall amount often exceeds 2000 mm. Predicting soil …