Application of fuzzy modelling and Particle Swarm Optimization to enhance lipid extraction from microalgae


Lipid extraction from microalgae is maximized by defining the optimal operating conditions of the microwave pretreatment method. Using the experimental data, a robust model that describes the lipid extraction is generated using fuzzy logic. Then, the optimal extraction conditions of the lipid are determined using Particle Swarm Optimization (PSO) algorithm. Three different operating parameters influence on the recovered lipid from Microalgae. These parameters are power (W), heating time (min), and extraction time (h). Accordingly, during the optimization process, these parameters are used as a decision variables for PSO optimizer in order to maximize the recovered lipid that used as a cost function. The resulting plots demonstrated a well-fitting between the fuzzy model and the experimental data. Based on the built model, the optimization process achieved a significant increase in the lipid extraction by 22% compared to that obtained experimentally and using the ANOVA.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
College of Engineering & Physical Sciences
Additional Information: © 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Uncontrolled Keywords: Biodiesel,Fuzzy-modeling,Lipid extraction,Microalga,Particle Swarm Optimization,Renewable Energy, Sustainability and the Environment,Energy Engineering and Power Technology
Publication ISSN: 2213-1388
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.sci ... 0104?via%3Dihub (Publisher URL)
PURE Output Type: Article
Published Date: 2019-10-01
Published Online Date: 2019-06-28
Accepted Date: 2019-06-21
Authors: Nassef, Ahmed M.
Rezk, Hegazy
Abdelkareem, Mohammad Ali
Alaswad, A. (ORCID Profile 0000-0002-7828-7924)
Olabi, A.

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