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Urban resilience and livability performance of European smart cities: A novel machine learning approach
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Elsevier
, 2022 , Article)
Smart cities are centres of economic opulence and hope for standardized living. Understanding the shades of urban resilience and livability in smart city models is of paramount importance. This study presents a novel ...
Shear capacity prediction of FRP-RC beams using single and ensenble ExPlainable Machine learning models
(
Elsevier
, 2022 , Article)
Corrosion in steel reinforcement is a central issue behind the severe deterioration of existing reinforced concrete (RC) structures. Nowadays, fiber-reinforced polymer (FRP) is increasingly being used as a viable alternative ...
Explainable machine learning model and reliability analysis for flexural capacity prediction of RC beams strengthened in flexure with FRCM
(
Elsevier
, 2022 , Article)
This paper presents a data-driven approach to determine the load and flexural capacities of reinforced concrete (RC) beams strengthened with fabric reinforced cementitious matrix (FRCM) composites in flexure. A total of ...
Machine learning-based shear capacity prediction and reliability analysis of shear-critical RC beams strengthened with inorganic composites
(
Elsevier
, 2022 , Article)
The application of inorganic composites has proven to be an effective strengthening technique for shear-critical reinforced concrete (RC) beams. However, accurate prediction of the shear capacity of RC beams strengthened ...
Blue collar laborers’ travel pattern recognition: Machine learning classifier approach
(
Elsevier
, 2021 , Article)
This paper proposes a pattern recognition model to develop clusters of homogenous activities for blue-collar workers in the State of Qatar. The activity-based data from the travel diary of 1051 blue-collar workers collected ...
FAI: Fast, accurate, and intelligent approach and prediction tool for flexural capacity of FRP-RC beams based on super-learner machine learning model
(
Elsevier
, 2022 , Article)
Fiber-reinforced polymer (FRP) composites have recently been considered in the field of structural engineering as one of the best alternatives to conventional steel reinforcement due to their high tensile strength, ...
Reconstruction of Road Defects from Dynamic Vehicle Accelerations by Using the Artificial Neural Networks
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Springer Science and Business Media B.V.
, 2023 , Conference Paper)
Monitoring of roads is considered the first step in establishing a successful road maintenance program, which includes scheduling adequate maintenance to a certain road section at the right time. Road monitoring assesses ...
Modeling of forward osmosis process using artificial neural networks (ANN) to predict the permeate flux
(
Elsevier
, 2020 , Article)
Artificial neural networks (ANN) are black box models that are becoming more popular than transport-based models due to their high accuracy and less computational time in predictions. The literature shows a lack of ANN ...
Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques
(
MDPI
, 2022 , Article)
Diabetes mellitus (DM) can lead to plantar ulcers, amputation and death. Plantar foot thermogram images acquired using an infrared camera have been shown to detect changes in temperature distribution associated with a ...
Modeling of permeability impairment dynamics in porous media: A machine learning approach
(
Elsevier
, 2023 , Article)
The prediction of clogging and permeability impairment dynamics in porous media is crucial for the optimization of various industrial and natural processes. This paper presents a novel machine learning-based approach for ...