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A fuzzy model was designed to predict changes in surface tension and maximum absorbance due to self-assembly in a DMF solution of poly{1,1′-ferrocene-diamide-[1,3-bis(propylene) tetramethyl-disiloxane} as a function of temperature and concentration. The building of fuzzy rule-based inference systems appears as a grey-box because it allows interpretation of the knowledge contained in the model as well as its improvement with a-priori knowledge. The method provides accurate results and increases the efficiency of utilizing the available information in the model. Small mean squared errors (0.0064 for absorbance and 0.79 for surface tension) and strong correlations between experiment and simulated results (0.93 and 0.97, respectively) were found during model validation. The results showed that it is feasible to apply a Mamdani fuzzy inference system to the estimation of optical and surface properties of a ferrocenylsiloxane polyamide solution.
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