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Which method is better for the kinetic modeling:Decimal encoded or Binary Genetic Algorithm?

机译:哪种方法更适合动力学建模:十进制编码或二进制遗传算法?

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Kinetic modeling is an important issue,whose objective is the accurate determination of the rates of various reactions taking place in a reacting system.This issue is a pivotal element for the process design and development particularly for novel processes which are based on reactions taking place between various types of species.In this paper,the Genetic Algorithms have been used to develop a systematic computational framework for kinetic modeling of various reacting systems.This framework can be used to find the optimum values of various parameters that exist in the kinetic model of a reacting system.The Fischer-Tropsch (FT) reactions have been used as the kinetic modeling bench mark.General kinetic models for FT,Water-Gas-shift (WGS) and overall rates based on Langmuir-Hinshelwood type have been considered and their optimum parameters have been obtained by Genetic Algorithms.The study shows the obtained model outperforms the other alternative models both in generality and accuracy.Furthermore,the performance of Binary and Decimal Genetic Algorithms have been compared.The obtained results show that despite its ease of implementation,Decimal encoding GA has lower performance comparing to Binary encoding GA.
机译:动力学建模是一个重要的问题,其目的是准确确定反应系统中发生的各种反应的速率。该问题是过程设计和开发的关键要素,特别是对于基于反应之间发生的反应的新颖过程本文使用遗传算法为各种反应系统的动力学建模开发了系统的计算框架,该框架可用于找到存在于一个动力学模型中的各种参数的最优值。 Fischer-Tropsch(FT)反应已被用作动力学建模基准.FT的一般动力学模型,水气转换(WGS)和基于Langmuir-Hinshelwood类型的总速率已被考虑并达到最佳通过遗传算法获得了参数,研究表明所获得的模型在通用性和准确性上均优于其他模型。结果表明,尽管十进制编码遗传算法易于实现,但与二进制编码遗传算法相比性能较低。

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