Machine learning approach for predicting crude oil stability based on NMR spectroscopy

An Inferable Machine Learning Approach to Predicting PVT Properties of Niger Delta Crude Oil using Compositional Data

10.2118/199783-stu ◽

2019 ◽

Author(s):

Oluwapelumi Sola-Aremu

Keyword(s):

Machine Learning ◽

Crude Oil ◽

Niger Delta ◽

Compositional Data ◽

Learning Approach ◽

Pvt Properties ◽

A machine learning approach to detect crude oil contamination in a real scenario using hyperspectral remote sensing

International Journal of Applied Earth Observation and Geoinformation ◽

10.1016/j.jag.2019.101901 ◽

2019 ◽

Vol 82 ◽

pp. 101901 ◽

Cited By ~ 9

Author(s):

Ran Pelta ◽

Nimrod Carmon ◽

Eyal Ben-Dor

Keyword(s):

Machine Learning ◽

Remote Sensing ◽

Crude Oil ◽

Hyperspectral Remote Sensing ◽

Oil Contamination ◽

Learning Approach ◽

Crude Oil Contamination ◽

Real Scenario

Efficiency Check Using Cointegration and Machine Learning Approach: Crude Oil Futures Markets

Procedia Computer Science ◽

10.1016/j.procs.2021.07.038 ◽

2021 ◽

Vol 191 ◽

pp. 304-311

Author(s):

Siddak Singh Bakshi ◽

Raj K Jaiswal ◽

Ritika Jaiswal

Keyword(s):

Machine Learning ◽

Crude Oil ◽

Futures Markets ◽

Learning Approach ◽

Oil Futures ◽

Crude Oil Futures

Machine learning approach for crude oil price prediction with Artificial Neural Networks-Quantitative (ANN-Q) model

The 2010 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2010.5596602 ◽

2010 ◽

Cited By ~ 17

Author(s):

S. N. Abdullah ◽

X. Zeng

Keyword(s):

Machine Learning ◽

Neural Networks ◽

Artificial Neural Networks ◽

Crude Oil ◽

Oil Price ◽

Learning Approach ◽

Crude Oil Price ◽

Price Prediction ◽

Q Model

Constructing and Validating Geographically Refined HAZUS-MH4 Hurricane Wind Risk Models: A Machine Learning Approach

Advances in Hurricane Engineering ◽

10.1061/9780784412626.092 ◽

2012 ◽

Cited By ~ 2

Author(s):

D. Subramanian ◽

J. Salazar ◽

L. Duenas-Osorio ◽

R. Stein

Keyword(s):

Machine Learning ◽

Learning Approach ◽

Risk Models ◽

Hurricane Wind ◽

The impact of economic plans on the Chinese education system: a machine learning approach

CADMO ◽

10.3280/cad2018-001005 ◽

2018 ◽

pp. 37-49

Author(s):

Wenjun Lin ◽

Xuefu Xu ◽

Francesco Dell’Anna

Keyword(s):

Machine Learning ◽

Education System ◽

Learning Approach ◽

Chinese Education ◽

System A ◽

The Impact

Improving Bandwidth Utilization and Fairness between TCP Flows based on a Machine-learning Approach

IEEJ Transactions on Electronics Information and Systems ◽

10.1541/ieejeiss.133.1259 ◽

2013 ◽

Vol 133 (6) ◽

pp. 1259-1268

Author(s):

Akihiro Shiozu ◽

Syunji Yazaki ◽

K^|^ocirc;ki Abe

Keyword(s):

Machine Learning ◽

Learning Approach ◽

Bandwidth Utilization ◽

A Machine Learning Approach to Anaphora Resolution in Arabic

International Review on Computers and Software (IRECOS) ◽

10.15866/irecos.v9i12.4786 ◽

2014 ◽

Vol 9 (12) ◽

pp. 1956

Author(s):

Abdullatif Abolohom ◽

Nazlia Omar

Keyword(s):

Machine Learning ◽

Learning Approach ◽

Anaphora Resolution ◽

1552-P: Machine Learning Approach to Decision-Making for Initial Insulin Use in Japanese Patients with Type 2 Diabetes

Diabetes ◽

10.2337/db20-1552-p ◽

2020 ◽

Vol 69 (Supplement 1) ◽

pp. 1552-P

Author(s):

KAZUYA FUJIHARA ◽

MAYUKO H. YAMADA ◽

YASUHIRO MATSUBAYASHI ◽

MASAHIKO YAMAMOTO ◽

TOSHIHIRO IIZUKA ◽

...

Keyword(s):

Machine Learning ◽

Type 2 Diabetes ◽

Decision Making ◽

Japanese Patients ◽

Learning Approach ◽

Insulin Use

A Machine Learning Approach to Jet-Surface Interaction Noise Modeling

AIAA Scitech 2020 Forum ◽

10.2514/6.2020-1728 ◽

2020 ◽

Author(s):

Clifford A. Brown ◽

Jonny Dowdall ◽

Brian Whiteaker ◽

Lauren McIntyre

Keyword(s):

Machine Learning ◽

Surface Interaction ◽

Learning Approach ◽

Noise Modeling ◽