Prediction of air quality index using machine learning techniques: a comparative analysis

NS Gupta, Y Mohta, K Heda, R Armaan… - … and Public Health, 2023 - Wiley Online Library
An index for reporting air quality is called the air quality index (AQI). It measures the impact
of air pollution on a person's health over a short period of time. The purpose of the AQI is to …

Machine-learning predictions of solubility and residual trap** indexes of carbon dioxide from global geological storage sites

S Davoodi, HV Thanh, DA Wood, M Mehrad… - Expert Systems with …, 2023 - Elsevier
Ongoing anthropogenic carbon dioxide (CO 2) emissions to the atmosphere cause severe
air pollution that leads to complex changes in the climate, which pose threats to human life …

Hybridized machine-learning for prompt prediction of rheology and filtration properties of water-based drilling fluids

S Davoodi, M Mehrad, DA Wood, H Ghorbani… - … Applications of Artificial …, 2023 - Elsevier
Careful design and preparation of drilling fluids with appropriate rheology and filtration
properties, combined with operational monitoring, is essential for successful drilling …

Predicting shear wave velocity from conventional well logs with deep and hybrid machine learning algorithms

M Rajabi, O Hazbeh, S Davoodi, DA Wood… - Journal of Petroleum …, 2023 - Springer
Shear wave velocity (VS) data from sedimentary rock sequences is a prerequisite for
implementing most mathematical models of petroleum engineering geomechanics …

Optimized machine learning models for natural fractures prediction using conventional well logs

S Tabasi, PS Tehrani, M Rajabi, DA Wood, S Davoodi… - Fuel, 2022 - Elsevier
Identifying and characterizing natural fractures is essential for understanding fluid flow and
drainage in many oil and gas reservoirs, particularly carbonate. The presence of fractures …

Machine learning insights to CO2-EOR and storage simulations through a five-spot pattern–a theoretical study

S Davoodi, HV Thanh, DA Wood, M Mehrad… - Expert Systems with …, 2024 - Elsevier
The utilization of CO 2 flooding is a widely applied enhanced oil recovery (EOR) technique
in mature onshore oil fields. As well as being able to increase oil production and recovery it …

Short-term power load forecasting based on Seq2Seq model integrating Bayesian optimization, temporal convolutional network and attention

Y Dai, W Yu - Applied Soft Computing, 2024 - Elsevier
Power load forecasting is of great significance to the electricity management. However,
extant research is insufficient in comprehensively combining data processing and further …

[HTML][HTML] A robust approach to pore pressure prediction applying petrophysical log data aided by machine learning techniques

G Zhang, S Davoodi, SS Band, H Ghorbani, A Mosavi… - Energy Reports, 2022 - Elsevier
Determination of pore pressure (PP), a key reservoir parameter that is beneficial for
evaluating geomechanical parameters of the reservoir, is so important in oil and gas fields …

Smart predictive viscosity mixing of CO2–N2 using optimized dendritic neural networks to implicate for carbon capture utilization and storage

AA Ewees, HV Thanh, MAA Al-qaness… - Journal of …, 2024 - Elsevier
Crucial for carbon capture, utilization, and storage (CCUS) initiatives and diverse industries,
heat transfer underscores the need for a precise assessment of carbon dioxide (CO 2) and …

[HTML][HTML] Deep eutectic solvent viscosity prediction by hybrid machine learning and group contribution

A Roosta, R Haghbakhsh, ARC Duarte… - Journal of Molecular …, 2023 - Elsevier
In this study, hybrid machine learning nonlinear models were developed to predict the
viscosity of DESs by combining the group contribution (GC) concept with the multilayer …