Abstract
This paper proposes the fitness diversity based adaptive memetic algorithm (FIDAMA) for solving the problem of the inverse type consisting of retrieving chemical kinetics reaction rate coefficients in the generalised Arrhenius form based on the observed concentrations in a given range of temperatures of a limited set of species which describe the reaction mechanism. FIDAMA consists of the evolutionary framework and three local searchers adaptively governed by a novel fitness diversity based measure. Moreover, a certain simplification of the decision space was carried out without any deterioration in the result obtained. The numerical results preseted show the superiority of FIDAMA compared to the other published computational intelligence methods.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
