Heat transfer dynamics modelling by means of clustering and swarm methods Online publication date: Thu, 01-Aug-2019
by Oualid Lamraoui; Yassine Boudouaoui; Hacene Habbi
International Journal of Intelligent Engineering Informatics (IJIEI), Vol. 7, No. 4, 2019
Abstract: This paper deals with the modelling problem of heat transfer dynamics in thermal exchanger process by using fuzzy prediction approaches. Clustering and swarm-based optimisation methods are used to derive heat transfer dynamical models to predict temperature variations of hot and cold fluids in the exchanger. The clustering method relies on a one-shot potential calculating strategy to extract the fuzzy sets distribution from the data space. However, the swarm optimisation method employs a subject function to optimise the premise and conclusion parameters of the fuzzy structure. Experimental data extracted from a pilot exchanger process is used to learn the fuzzy models, and their performances are compared on both training and testing measurement data.
Online publication date: Thu, 01-Aug-2019
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