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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 ...
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, ...
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 ...
Forecasting the impact of environmental stresses on the frequent waves of COVID19
(
Springer
, 2021 , Article)
A novel approach to link the environmental stresses with the COVID-19 cases is adopted during this research. The time-dependent data are extracted from the online repositories that are freely available for knowledge and ...
Power transformer health condition evaluation: A deep generative model aided intelligent framework
(
Elsevier Ltd
, 2023 , Article)
This paper presents a deep generative model-aided intelligent framework for effective health condition evaluation of power grid transformers. The health assessment of a power transformer is required to guarantee the stable ...
Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects
(
Elsevier B.V.
, 2022 , Article Review)
In modern Smart Grids (SGs) ruled by advanced computing and networking technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this connection, a portion of transported data, containing ...
Machine learning in the Internet of Things: Designed techniques for smart cities
(
Elsevier B.V.
, 2019 , Article)
Machine learning is one of the emerging technologies that has grabbed the attention of academicians and industrialists, and is expected to evolve in the near future. Machine learning techniques are anticipated to provide ...
Breast cancer image classification using pattern-based Hyper Conceptual Sampling method
(
Elsevier Ltd
, 2018 , Article)
The increase in biomedical data has given rise to the need for developing data sampling techniques. With the emergence of big data and the rise of popularity of data science, sampling or reduction techniques have been ...
A machine learning framework for enhancing digital experiences in cultural heritage
(
Emerald Group Publishing Ltd.
, 2020 , Article)
Purpose: Digital tools have been used to document cultural heritage with high-quality imaging and metadata. However, some of the historical assets are totally or partially unlabeled and some are physically damaged, which ...