Results 141 to 150 of about 52,233 (277)

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

Synonym‐based multi‐keyword ranked search with secure k‐NN in 6G network

IET Networks, EarlyView., 2022
Abstract Sixth Generation (6G) integrates the next generation communication systems such as maritime, terrestrial, and aerial to offer robust network and massive device connectivity with ultra‐low latency requirement. The cutting edge technologies such as artificial intelligence, quantum machine learning, and millimetre enable hyper‐connectivity to ...
Deebak Bakkiam David, Fadi Al‐Turjman
wiley   +1 more source

Geostatistical Analysis of Seabed Sediment Type: A Compositional Approach with Non-Euclidean Distance Metrics. [PDF]

Math Geosci
Goovaerts P.
europepmc   +1 more source

Unlocking the Multifunctional Properties of Litsea cubeba Essential Oil: Composition, Antimicrobial, Antibiofilm and Insecticidal Activities

Flavour and Fragrance Journal, EarlyView.
Unveiling the chemical and biological properties of Litsea cubeba essential oil. ABSTRACT Litsea cubeba essential oil (LCEO) is recognised for its broad spectrum of biological activities, including antimicrobial and insecticidal effects, making it a promising natural alternative to synthetic agents.
Miroslava Kačániová, Minhang Qiao, Alessandro Bianchi, Joel Horacio Elizondo‐Luevano, Anis Ben Hsouna, Rania Ben Saad, Zhaojun Ban, Li Li, Jian Lou, Wissem Mnif, Stefania Garzoli   +10 more
wiley   +1 more source

Intent Arabic text categorisation based on different machine learning and term frequency

IET Networks, EarlyView., 2022
Abstract The complexity of Internet network configurations has made managing networks a complicated undertaking. Intent‐Based Networking (IBN) is a potential solution to this issue. In contrast to conventional networks, where a concrete description of the settings typically conveys a network administrator's goal kept on each device, an administrator's ...
Mohammad Fadhil Mahdi, Mahmoud Shuker Mahmoud   +1 more
wiley   +1 more source

Generation of severely scoliotic subject-specific musculoskeletal models. [PDF]

PLoS One
Gould SL, Davico G, Cosentino M, Cristofolini L, Viceconti M.   +4 more
europepmc   +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

Lost in Translation? Risk‐Adjusting RMSE for Economic Forecast Performance

Journal of Forecasting, EarlyView.
ABSTRACT When used for parameter optimization and/or model selection, traditional mean squared error (MSE)–based measures of forecast accuracy often exhibit a weak or even negative correlation with the economic value of return forecasts measured by, for example, the Sharpe ratios of the resulting portfolios.
Lukas Salcher, Sebastian Stöckl, Michael Hanke   +2 more
wiley   +1 more source

Minimum Spacetime Length and the Thermodynamics of Spacetime. [PDF]

Entropy (Basel)
Rossi V, Cacciatori SL, Pesci A.
europepmc   +1 more source

Creation of a Landslide Susceptibility Map Using Short‐Term Data From the July 2018 Heavy Rainfall in Southern Hiroshima Prefecture

Geological Journal, EarlyView.
This work advances landslide susceptibility mapping by incorporating short‐term trigger data with landscape susceptibility mapping. We also examine the importance of downsampling, watershed delineation and geospatial correlations in evaluating outcomes.
Kanta Kotsugi, Ting Liu, Toshiro Hata, Rebecca Muenich   +3 more
wiley   +1 more source