Application of extreme learning machine for prediction of aqueous solubility of carbon dioxide

CO2 Storage in Low Permeable Carbonate Reservoirs: Permeability and Interfacial Tension (IFT) Changes During CO2 Injection in an Iranian Carbonate Reservoir

“…CO 2 solubility and reactivity increases with pressure. Previous studies have pointed out that a decrease in pH of the brine can be observed as the dissolution of CO 2 in brine is elevated by pressure, which creates a favorable condition for rock dissolution to occur [11,[47][48][49][50]. Therefore, in order to link the changes of permeability to the rock dissolution, the pH of effluents as well as calcium concentrations had to be determined after each coreflood experiment.…”

“…At constant injection pressure, increasing the confining pressure also increases the effective stress on the rock mass, which consequently reduces the pore space and caused rocks to shrink. This eventually increases the rock mass tortuosity for CO 2 movement, thereby resulting in reduced effective CO 2 permeability in the rock mass [47][48][49][50][51]. Fig.…”

Influential Factor Analysis and Projection of Industrial CO₂ Emissions in China Based on Extreme Learning Machine Improved by Genetic Algorithm

“…(3) The ELM and GA-ELM algorithms are widely used in forecasting. For example, for predicting ionic liquid viscosity [37], the monthly effective drought index [38], carbon dioxide water solubility [39], the ionic liquid refractive index [40], gas emissions (41), solar radiation [42], wind power fluctuation range [43], the critical flow rate of mud pipeline transportation [44] and so on. The GA-ELM algorithm can be widely used in different fields for prediction, which shows that this prediction model has obvious advantages.…”

“…The prediction of the monthly effective drought index [38], through the ELM model, improved the prediction of drought duration and severity, and found that ELM is a faster tool for predicting drought and its related characteristics. The prediction of water solubility of carbon dioxide [39], comparing the estimation and prediction results of the ELM model with genetic programming (GP) and artificial neural network (ANN) models, the ELM model can be used safely to develop new water-soluble carbon dioxide. For the refractive index of ionic liquids [40], the average absolute relative deviation of the results predicted by ELM is only 0.295%.…”

Retraction Note to: Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam

“…The Editor-in-Chief has retracted this article (Toghroli et al 2018) because validity of the content of this article cannot be verified. This article showed evidence of substantial text overlap (most notably with the articles cited Cojbasic et al 2016;Mazinani et al 2016;Mohammadian et al 2016;Mansourvar et al 2015) and authorship manipulation. Meldi Suhatril, Zainah Ibrahim, Maryam Safa, Mahdi Shariati and Shahaboddin Shamshirband do not agree to this retraction.…”