Results 141 to 150 of about 77,058 (245)

Machine Learning‐Driven Classification and Production Capacity Prediction of Tight Sandstone Reservoirs: A Case Study of the Taiyuan Formation, Ordos Basin

Energy Science &Engineering, EarlyView.
On the basis of core and log data, a Bayesian‐Optimized Random Forest model achieved 92.76% accuracy in classifying tight sandstone reservoirs. A gray relational analysis‐derived evaluation index shows > 80% consistency with actual gas zones. ABSTRACT Tight sandstone gas (TSG), an unconventional oil–gas resource, has heterogeneous reservoirs ...
Yin Yuan, Haijiao Fu, Detian Yan, Gang Wang, Shuguang Yang, Mengmeng Liu, Qingling Jiang, Xiaoming Wang, Wei Wang   +8 more
wiley   +1 more source

Sigscores: summary scores for molecular signatures in R. [PDF]

Bioinform Adv
Barberis A, Buffa FM.
europepmc   +1 more source

Mono‐dimensional, two‐dimensional and Doppler echocardiographic measurements in healthy Standardbred neonatal foals in the first 5 days of life

Equine Veterinary Journal, EarlyView.
Abstract Background Bodyweight, age and breed influence the echocardiographic assessment of foals. There are no echocardiographic studies in Standardbred neonatal foals. Objectives To describe echocardiographic values for selected variables, evaluate intra‐ and inter‐observer variability and assess cardiac changes in the first 5 days of life in healthy
Fernanda Timbó D'el Rey Dantas, Giulia Forni, Gayle Hallowell, Carolina Castagnetti, Laura Menchetti, Giovanni Romito, Aliai Lanci, Jole Mariella, Francesca Freccero   +8 more
wiley   +1 more source

Computationally efficient tail distribution-aware large-scale power system overloading risk assessment. [PDF]

Nat Commun
Tan B, Ye K, Zhao J, Hong M, Maslennikov S, Luo X.   +5 more
europepmc   +1 more source

Risk assessment for condylar stress fracture in elite racing Thoroughbreds using standing computed tomography‐based virtual mechanical testing

Equine Veterinary Journal, EarlyView.
Abstract Background Condylar stress fracture of the third metacarpal bone (MC3) is a common catastrophic injury in Thoroughbred racehorses and is associated with parasagittal groove (PSG) subchondral osteolysis. Standing computed tomography (sCT) imaging enables sensitive identification of this fatigue‐induced early subchondral bone injury (SBI), but ...
Nicola L. Brown, Soroush Irandoust, Elleana J. Thom, R. Christopher Whitton, Corinne R. Henak, Peter Muir   +5 more
wiley   +1 more source

Pruning tree forest and re-sampling for class imbalanced problem. [PDF]

Sci Rep
Faiz N, Iftikhar S, Jan S, Hamraz M, Aamir M, Khan DM.   +5 more
europepmc   +1 more source

What happened after the epidemic? Equine influenza surveillance sheds light on sources and seasonal risk in the United Kingdom

Equine Veterinary Journal, EarlyView.
Abstract Background The epidemiology of equine influenza (EI) in the United Kingdom has not been systematically described since the 2019 epidemic. Objectives To summarise UK EI surveillance (2020–2024), quantify outbreak seasonality and assess movement‐related sources. Study Design Retrospective observational analysis of national surveillance and horse
Fleur Whitlock, John Grewar, Richard Newton   +2 more
wiley   +1 more source

Local Polynomial Regression and Filtering for a Versatile Mesh‐Free PDE Solver

International Journal for Numerical Methods in Fluids, EarlyView.
A high‐order, mesh‐free finite difference method for solving differential equations is presented. Both derivative approximation and scheme stabilisation is carried out by parametric or non‐parametric local polynomial regression, making the resulting numerical method accurate, simple and versatile. Numerous numerical benchmark tests are investigated for
Alberto M. Gambaruto
wiley   +1 more source

Near-Optimal Decoding Algorithm for Color Codes Using Population Annealing. [PDF]

Entropy (Basel)
Martínez-García F, F Pereira FR, Parrado-Rodríguez P.   +2 more
europepmc   +1 more source

Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer, Kristofer Månsson, Pär Sjölander, Gazi Salah Uddin   +3 more
wiley   +1 more source