Prediction of clathrate hydrate phase equilibria using gradient boosted regression trees and deep neural networks

Hydrate Phase ◽

Semi-clathrate hydrate phase equilibria of carbon dioxide in presence of tetra-n-butyl-ammonium chloride (TBAC): Experimental measurements and thermodynamic modeling

Fluid Phase Equilibria ◽

10.1016/j.fluid.2019.112445 ◽

2020 ◽

Vol 508 ◽

pp. 112445

Author(s):

Kamalodin Momeni ◽

Abolfazl Jomekian ◽

Bahamin Bazooyar

Keyword(s):

Carbon Dioxide ◽

Phase Equilibria ◽

Ammonium Chloride ◽

Thermodynamic Modeling ◽

Clathrate Hydrate ◽

Experimental Measurements ◽

Multi-site solar power forecasting using gradient boosted regression trees

Solar Energy ◽

10.1016/j.solener.2017.04.066 ◽

2017 ◽

Vol 150 ◽

pp. 423-436 ◽

Cited By ~ 87

Author(s):

Caroline Persson ◽

Peder Bacher ◽

Takahiro Shiga ◽

Henrik Madsen

Keyword(s):

Solar Power ◽

Regression Trees ◽

Gradient Boosted Regression Trees ◽

Solar Power Forecasting ◽

Power Forecasting

Methane Semi-Clathrate Hydrate Phase Equilibria with Tetraisopentylammonium Fluoride

Journal of Chemical & Engineering Data ◽

10.1021/je200538d ◽

2011 ◽

Vol 56 (12) ◽

pp. 4597-4603 ◽

Cited By ~ 11

Author(s):

Thomas J. Hughes ◽

Kenneth N. Marsh

Keyword(s):

Phase Equilibria ◽

Clathrate Hydrate ◽

Prediction of higher heating value of biomass materials based on proximate analysis using gradient boosted regression trees method

Energy Sources Part A Recovery Utilization and Environmental Effects ◽

10.1080/15567036.2019.1630521 ◽

2019 ◽

Vol 43 (6) ◽

pp. 672-681 ◽

Cited By ~ 6

Author(s):

Seyed Hashem Samadi ◽

Barat Ghobadian ◽

Mohsen Nosrati

Keyword(s):

Regression Trees ◽

Proximate Analysis ◽

Heating Value ◽

Biomass Materials ◽

PredPRBA: Prediction of Protein-RNA Binding Affinity Using Gradient Boosted Regression Trees

Frontiers in Genetics ◽

10.3389/fgene.2019.00637 ◽

2019 ◽

Vol 10 ◽

Cited By ~ 3

Author(s):

Lei Deng ◽

Wenyi Yang ◽

Hui Liu

Keyword(s):

Binding Affinity ◽

Rna Binding ◽

Regression Trees ◽

Accurate prediction of clathrate hydrate phase equilibria below 300 K from a simple model

Journal of Petroleum Science and Engineering ◽

10.1016/j.petrol.2005.11.008 ◽

2006 ◽

Vol 51 (1-2) ◽

pp. 45-53 ◽

Cited By ~ 18

Author(s):

Yanfeng Zhang ◽

Pablo G. Debenedetti ◽

Robert K. Prud'homme ◽

Brian A. Pethica

Keyword(s):

Simple Model ◽

Phase Equilibria ◽

Clathrate Hydrate ◽

Accurate Prediction ◽

Wind ramp event prediction with parallelized gradient boosted regression trees

2016 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2016.7727900 ◽

2016 ◽

Cited By ~ 3

Author(s):

Saurav Gupta ◽

Nitin Anand Shrivastava ◽

Abbas Khosravi ◽

Bijaya Ketan Panigrahi

Keyword(s):

Regression Trees ◽

Event Prediction ◽

CLATHRATE HYDRATE PHASE EQUILIBRIA FOR CARBONYL SULFIDE, HYDROGEN SULFIDE, ETHYLENE, OR PROPANE + WATER SYSTEM BELOW WATER FREEZING POINT

Chemical Engineering Communications ◽

10.1080/00986445.2012.757550 ◽

2013 ◽

Vol 200 (12) ◽

pp. 1635-1644 ◽

Cited By ~ 7

Author(s):

Amir H. Mohammadi ◽

Dominique Richon

Keyword(s):

Hydrogen Sulfide ◽

Phase Equilibria ◽

Freezing Point ◽

Carbonyl Sulfide ◽

Water System ◽

Clathrate Hydrate ◽

Estimation of real-driving emissions for buses fueled with liquefied natural gas based on gradient boosted regression trees

The Science of The Total Environment ◽

10.1016/j.scitotenv.2019.01.054 ◽

2019 ◽

Vol 660 ◽

pp. 741-750 ◽

Cited By ~ 40

Author(s):

Yingjiu Pan ◽

Shuyan Chen ◽

Fengxiang Qiao ◽

Satish V. Ukkusuri ◽

Kun Tang

Keyword(s):

Natural Gas ◽

Regression Trees ◽

Liquefied Natural Gas ◽

Pressure drop modelling in sand filters in micro-irrigation using gradient boosted regression trees

Biosystems Engineering ◽

10.1016/j.biosystemseng.2018.04.011 ◽

2018 ◽

Vol 171 ◽

pp. 41-51 ◽

Cited By ~ 5

Author(s):

Paulino J. García Nieto ◽

Esperanza García–Gonzalo ◽

Gerard Arbat ◽

Miquel Duran–Ros ◽

Francisco Ramírez de Cartagena ◽

...

Keyword(s):

Pressure Drop ◽

Regression Trees ◽

Sand Filters ◽

Micro Irrigation ◽