A systematic review of data science and machine learning applications to the oil and gas industry
This study offered a detailed review of data sciences and machine learning (ML) roles in
different petroleum engineering and geosciences segments such as petroleum exploration …
different petroleum engineering and geosciences segments such as petroleum exploration …
Revolutionizing concrete analysis: An in-depth survey of AI-powered insights with image-centric approaches on comprehensive quality control, advanced crack …
Over the last two decades, the integration of big data and deep learning technologies has
demonstrated remarkable effectiveness across various domains of civil engineering, leading …
demonstrated remarkable effectiveness across various domains of civil engineering, leading …
Predicting the compressive strength of concrete containing metakaolin with different properties using ANN
The advantages of using Metakaolin (MK) as a supplementary cementitious material have
led this highly active pozzolan to be widely used in the concrete industry. Awareness of the …
led this highly active pozzolan to be widely used in the concrete industry. Awareness of the …
Compressive strength prediction of high-performance concrete using gradient tree boosting machine
In structural engineering, concrete compressive strength (CCS) is the most important
performance parameter for designing the conventional concrete and high-performance …
performance parameter for designing the conventional concrete and high-performance …
A comparative investigation using machine learning methods for concrete compressive strength estimation
Concrete compressive strength plays an important role in determining the mechanical
properties of concrete. The determination of concrete compressive strength requires lengthy …
properties of concrete. The determination of concrete compressive strength requires lengthy …
Super learner machine‐learning algorithms for compressive strength prediction of high performance concrete
Because the proportion between the compressive strength of high‐performance concrete
(HPC) and its composition is highly nonlinear, more advanced regression methods are …
(HPC) and its composition is highly nonlinear, more advanced regression methods are …
Properties prediction of environmentally friendly ultra-high-performance concrete using artificial neural networks
J Abellán García, J Fernández Gómez… - European Journal of …, 2022 - Taylor & Francis
Ultra-high-performance concrete (UHPC) results from the mixture of several constituents,
leading to a highly complex material in both, fresh and hardened state. The higher number …
leading to a highly complex material in both, fresh and hardened state. The higher number …
Random forest-based optimization of UHPFRC under ductility requirements for seismic retrofitting applications
J Abellan-Garcia, JS Guzmán-Guzmán - Construction and Building …, 2021 - Elsevier
UHPFRC is a material that offers several openings within the building industry. One of those
applications is the seismic retrofitting of existing non-ductile concrete structures. This paper …
applications is the seismic retrofitting of existing non-ductile concrete structures. This paper …
Four-layer perceptron approach for strength prediction of UHPC
J Abellán-García - Construction and Building Materials, 2020 - Elsevier
This research is aimed to develop a four-layer multi-layer-perceptron (MLP) model for
predicting the compressive strength of ultra-high-performance concrete (UHPC), regardless …
predicting the compressive strength of ultra-high-performance concrete (UHPC), regardless …
Comparison of machine learning techniques for the prediction of compressive strength of concrete
A comparative analysis for the prediction of compressive strength of concrete at the ages of
28, 56, and 91 days has been carried out using machine learning techniques via “R” …
28, 56, and 91 days has been carried out using machine learning techniques via “R” …