Phase Equilibrium Modeling of Clathrate Hydrates of Carbon Dioxide + 1,4-Dioxine Using Intelligent Approaches

In this work, an adaptive neuro-fuzzy inference system (ANFIS) and a couple of fuzzy logic approach and genetic algorithms are utilized to serve robust inverse-based approaches for determination/prediction of the clathrate hydrate formation pressure of carbon dioxide in the presence of 1,4-dioxine, which is a most-widely implemented water soluble organic promoter. The gained outcomes prove the reliability and accuracy of the suggested ANFIS approach with the mean square error of 0.0034 and squared correlation coefficients of 0.9969. Thanks to the results generated by the aforementioned intelligent approaches, the models proposed in the current research contribute to high accuracy for the estimations of the phase equilibria clathrate hydrates of carbon dioxide +1,4-dioxane.