All Stories

  1. Rigorous model for determination of PVT properties of crude oil in operational conditions

    Article • Energy Sources Part A Recovery Utilization and Environmental Effects, October 2019, Taylor & Francis

    Dr Alireza Baghban

  2. On the estimation of higher heating value of municipal wastes using soft computing approaches

    Article • Energy Sources Part A Recovery Utilization and Environmental Effects, July 2019, Taylor & Francis

    Dr Alireza Baghban, Dr S shamshirband

  3. QSPR based ANFIS model for predicting standard molar chemical exergy of organic materials

    Article • Petroleum Science and Technology, June 2019, Taylor & Francis

    Dr Alireza Baghban, Mohamadtaghi Rahimi

  4. On the prediction of solubility of alkane in carbon dioxide using the LSSVM algorithm

    Article • Petroleum Science and Technology, March 2019, Taylor & Francis

    Dr Alireza Baghban

  5. Modeling vaporization enthalpy of pure hydrocarbons and petroleum fractions using LSSVM approach

    Article • Energy Sources Part A Recovery Utilization and Environmental Effects, March 2019, Taylor & Francis

    Dr Alireza Baghban

  6. Application of ANFIS and LSSVM strategies for estimating thermal conductivity enhancement of metal and metal oxide based nanofluids

    Article • Engineering Applications of Computational Fluid Mechanics, January 2019, Taylor & Francis

    Dr Alireza Baghban

  7. Application of a supervised learning machine for accurate prognostication of higher heating values of solid wastes

    Article • Energy Sources Part A Recovery Utilization and Environmental Effects, February 2018, Taylor & Francis

    Dr Alireza Baghban

  8. Modeling of CO2-brine interfacial tension: Application to enhanced oil recovery

    Article • Petroleum Science and Technology, November 2017, Taylor & Francis

    Dr Alireza Baghban

  9. Asphaltene deposition during flow through pipes: Parametric and inhibition analyses

    Article • Petroleum Science and Technology, November 2017, Taylor & Francis

    Dr Alireza Baghban

  10. Estimating water content of natural gas: A radial basis function neural network method

    Article • Petroleum Science and Technology, September 2017, Taylor & Francis

    Dr Alireza Baghban

  11. Kinetic modeling and laboratory investigation of catalytic toluene methylation to para-xylene

    Article • Petroleum Science and Technology, September 2017, Taylor & Francis

    Dr Alireza Baghban

  12. Viscosity estimation of mixed oil using RBF-ANN approach

    Article • Petroleum Science and Technology, September 2017, Taylor & Francis

    Dr Alireza Baghban, reza eghtedaei

  13. Estimation of wax deposition in the oil production units using RBF-ANN strategy

    Article • Petroleum Science and Technology, September 2017, Taylor & Francis

    Dr Alireza Baghban, reza eghtedaei

  14. Radial basis function artificial neural network model to estimate higher heating value of solid wastes

    Article • Energy Sources Part A Recovery Utilization and Environmental Effects, August 2017, Taylor & Francis

    Dr Alireza Baghban

  15. Prediction of solubility of ammonia in liquid electrolytes using Least Square Support Vector Machines

    Article • Ain Shams Engineering Journal, September 2016, Elsevier

    Dr Alireza Baghban

  16. Phase equilibrium modelling of natural gas hydrate formation conditions using LSSVM approach

    Article • Petroleum Science and Technology, August 2016, Taylor & Francis

    Dr Alireza Baghban

  17. Application of the ANFIS strategy to estimate vaporization enthalpies of petroleum fractions and pure hydrocarbons

    Article • Petroleum Science and Technology, August 2016, Taylor & Francis

    Dr Alireza Baghban

  18. Modelling of CO2separation from gas streams emissions in the oil and gas industries

    Article • Petroleum Science and Technology, July 2016, Taylor & Francis

    Dr Alireza Baghban

  19. Estimation of oil and gas properties in petroleum production and processing operations using rigorous model

    Article • Petroleum Science and Technology, July 2016, Taylor & Francis

    Dr Alireza Baghban, Dr Zainal Ahmad

  20. Computational intelligent strategies to predict energy conservation benefits in excess air controlled gas-fired systems

    Article • Applied Thermal Engineering, June 2016, Elsevier

    Dr Alireza Baghban, Dr Zainal Ahmad

  21. Modeling of true vapor pressure of petroleum products using ANFIS algorithm

    Article • Petroleum Science and Technology, May 2016, Taylor & Francis

    Dr Alireza Baghban, Dr Zainal Ahmad

  22. Estimation of natural gases water content using adaptive neuro-fuzzy inference system

    Article • Petroleum Science and Technology, May 2016, Taylor & Francis

    Dr Alireza Baghban, Dr Zainal Ahmad

  23. Modelling of gas to hydrate conversion for promoting CO2capture processes in the oil and gas industry

    Article • Petroleum Science and Technology, April 2016, Taylor & Francis

    Dr Alireza Baghban

  24. Evolving machine learning models to predict hydrogen sulfide solubility in the presence of various ionic liquids

    Article • Journal of Molecular Liquids, April 2016, Elsevier

    Dr Alireza Baghban

  25. Estimation of air dew point temperature using computational intelligence schemes

    Article • Applied Thermal Engineering, January 2016, Elsevier

    Dr Alireza Baghban

  26. Evolving simple-to-apply models for estimating thermal conductivity of supercritical CO2

    Article • International Journal of Ambient Energy, October 2015, Taylor & Francis

    Dr Alireza Baghban

  27. Phase equilibrium modeling of semi-clathrate hydrates of seven commonly gases in the presence of TBAB ionic liquid promoter based on a low parameter connectionist technique

    Article • The Journal of Supercritical Fluids, June 2015, Elsevier

    Dr Alireza Baghban

  28. Prediction carbon dioxide solubility in presence of various ionic liquids using computational intelligence approaches

    Article • The Journal of Supercritical Fluids, March 2015, Elsevier

    Dr Alireza Baghban

  29. Estimating hydrogen sulfide solubility in ionic liquids using a machine learning approach

    Article • The Journal of Supercritical Fluids, November 2014, Elsevier

    Dr Alireza Baghban