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用于间歇光照下微藻生长的韩氏模型参数:通过粒子群优化算法确定。

Han's model parameters for microalgae grown under intermittent illumination: Determined using particle swarm optimization.

作者信息

Pozzobon Victor, Perre Patrick

机构信息

LGPM, CentraleSupélec, Université Paris-Saclay, SFR Condorcet FR CNRS 3417, Centre Européen de Biotechnologie et de Bioéconomie (CEBB),3 rue des Rouges Terres 51110 Pomacle, France.

LGPM, CentraleSupélec, Université Paris-Saclay, SFR Condorcet FR CNRS 3417, Centre Européen de Biotechnologie et de Bioéconomie (CEBB),3 rue des Rouges Terres 51110 Pomacle, France.

出版信息

J Theor Biol. 2018 Jan 21;437:29-35. doi: 10.1016/j.jtbi.2017.10.010. Epub 2017 Oct 16.

Abstract

This work provides a model and the associated set of parameters allowing for microalgae population growth computation under intermittent lightning. Han's model is coupled with a simple microalgae growth model to yield a relationship between illumination and population growth. The model parameters were obtained by fitting a dataset available in literature using Particle Swarm Optimization method. In their work, authors grew microalgae in excess of nutrients under flashing conditions. Light/dark cycles used for these experimentations are quite close to those found in photobioreactor, i.e. ranging from several seconds to one minute. In this work, in addition to producing the set of parameters, Particle Swarm Optimization robustness was assessed. To do so, two different swarm initialization techniques were used, i.e. uniform and random distribution throughout the search-space. Both yielded the same results. In addition, swarm distribution analysis reveals that the swarm converges to a unique minimum. Thus, the produced set of parameters can be trustfully used to link light intensity to population growth rate. Furthermore, the set is capable to describe photodamages effects on population growth. Hence, accounting for light overexposure effect on algal growth.

摘要

这项工作提供了一个模型以及相关的参数集,可用于计算间歇光照下微藻种群的增长。韩氏模型与一个简单的微藻生长模型相结合,得出光照与种群增长之间的关系。模型参数是通过使用粒子群优化方法拟合文献中可用的数据集获得的。在他们的工作中,作者在闪烁条件下在营养物质过量的情况下培养微藻。用于这些实验的光/暗循环与光生物反应器中的光/暗循环非常接近,即从几秒到一分钟不等。在这项工作中,除了生成参数集外,还评估了粒子群优化的鲁棒性。为此,使用了两种不同的群体初始化技术,即在整个搜索空间中均匀分布和随机分布。两者都产生了相同的结果。此外,群体分布分析表明群体收敛到一个唯一的最小值。因此,所生成的参数集可以可靠地用于将光强度与种群增长率联系起来。此外,该参数集能够描述光损伤对种群增长的影响。因此,考虑了光过度暴露对藻类生长的影响。

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