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

Ahmed M. Nassef, Hegazy Rezk*, Mohammad Ali Abdelkareem, A. Alaswad, A. Olabi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)73-79
Number of pages7
JournalSustainable Energy Technologies and Assessments
Early online date28 Jun 2019
Publication statusPublished - 1 Oct 2019

Bibliographical note

© 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International


  • Biodiesel
  • Fuzzy-modeling
  • Lipid extraction
  • Microalga
  • Particle Swarm Optimization


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