Open Access

Table 5

Summary of the main activities involving artificial intelligence.

Year Activity Authors
2018a Developed a multi-layer feed-forward neural network algorithm to estimate the CO2 adsorption equilibrium in activated carbon Rostami et al.
2016 Studied an innovative Least Square Support Vector Machine (LS-SVM) algorithm to create a model capable of predicting the effective thermal conductivity in dry sandstones Rostami et al.
2017a Used the Genetic Programming (GP) method to estimate the interfacial tension between hydrocarbon/water in reservoirs Rostami et al.
2017c Performed a GP as a mathematical strategy to estimate the thermal conductivity of supercritical CO2 Rostami et al.
2017b Studied a GEP method to estimate the solubility of CO2 in processes of CO2 flooding in oil reservoirs Rostami et al.
2017 Developed a comparative study on the estimates of interfacial tension between CO2-brine from the GEP, LS-SVM, and DT modeling methods with the ANN Kamari et al.
2010 Applied the artificial neural network model to estimate the minimum amount of PVA needed to improve the polymer flooding process. Rezaian et al.
2016 Studied artificial neural network models to estimate the viscosity of polymer solutions of three commercial acrylamide-based polymers Kang et al.
2018b Used artificial intelligence to estimate the viscosity of PHPA solutions from neural network models. Rostami et al.
2018 Developed a MLP neural network model to predict the viscosities of PHPA-based nanopolymer systems and xanthan gum nanosystems Corredor-Rojas et al.

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