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Data on fuzzy logic based-modelling and optimization of recovered lipid from microalgae

机译:基于模糊逻辑的微藻回收脂质建模与优化数据

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摘要

This article presents the data of recovered lipid from microalgae using fuzzy logic based-modelling and particle swarm optimization (PSO) algorithm. The details of fuzzy model and optimization process were discussed in our work entitled “Application of Fuzzy Modelling and Particle Swarm Optimization to Enhance Lipid Extraction from Microalgae” (Nassef et al., 2019) [1]. The presented data are divided into two main parts. The first part represents the percentage of recovered lipid using fuzzy logic model and ANOVA. However, the second part shows the variation of the cost function (recovered lipid) for the 100 runs of PSO algorithm during optimization process. These data sets can be used as references to analyze the data obtained by any other optimization technique. The data sets are provided in the supplementary materials in .
机译:本文介绍了使用基于模糊逻辑的建模和粒子群优化(PSO)算法从微藻中回收脂质的数据。模糊模型和优化过程的细节在我们题为“模糊模型和粒子群优化在增强从微藻类脂质提取中的应用”的工作中进行了讨论(Nassef等,2019)[1]。呈现的数据分为两个主要部分。第一部分使用模糊逻辑模型和ANOVA表示回收脂质的百分比。但是,第二部分显示了优化过程中100次PSO算法运行的成本函数(回收的脂质)的变化。这些数据集可以用作分析通过任何其他优化技术获得的数据的参考。这些数据集在的补充材料中提供。

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