Oil-CO2MMP Determination in Competition of Neural Network, Support Vector Regression, and Committee Machine

Prediction of Poisson's Ratio from Conventional Well Log Data: A Committee Machine with Intelligent Systems Approach

(2013) M. Asoodeh   Energy Sources Part A-Recovery Utilization and Environmental Effects

Intelligent Isochronal Test Analysis

(2013) M. Asoodeh   PETROLEUM SCIENCE AND TECHNOLOGY

Investigation on Asphaltene Deposition Mechanisms during CO2 Flooding Processes in Porous Media: A Novel Experimental Study and a Modified Model Based on Multilayer Theory for Asphaltene Adsorption

(2012) Taraneh Jafari Behbahani et al.   ENERGY & FUELS

Prediction of crude oil viscosity curve using artificial intelligence techniques

(2012) M.A. Al-Marhoun et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Estimation of bubble point pressure from PVT data using a power-law committee with intelligent systems

(2012) Mojtaba Asoodeh et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

An improved method for calculating CO2 minimum miscibility pressure based on solubility parameter

(2012) Gloria Meyberg Nunes Costa et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Prediction of Compressional, Shear, and Stoneley Wave Velocities from Conventional Well Log Data Using a Committee Machine with Intelligent Systems

(2011) Mojtaba Asoodeh et al.   ROCK MECHANICS AND ROCK ENGINEERING

An investigation on the applicability of Parachor model for the prediction of MMP using five equations of state

(2010) S.N. Ashrafizadeh et al.   CHEMICAL ENGINEERING RESEARCH & DESIGN

Support vector regression for porosity prediction in a heterogeneous reservoir: A comparative study

(2010) A.F. Al-Anazi et al.   COMPUTERS & GEOSCIENCES

Minimum miscibility pressure prediction based on a hybrid neural genetic algorithm

(2008) S.A. Mousavi Dehghani et al.   CHEMICAL ENGINEERING RESEARCH & DESIGN

Forecasting dissolved gases content in power transformer oil based on support vector machine with genetic algorithm

(2007) Sheng-Wei Fei et al.   ELECTRIC POWER SYSTEMS RESEARCH