Neural Network Based On the Improved Genetic Algorithm to Optimize Component Separation Conditions of Small Peptide

Jing Wen Tian; Feng Jun Wu; Hui Chen; Jing Di Ren

doi:10.4028/www.scientific.net/AMR.284-286.261

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 284-286Neural Network Based On the Improved Genetic...

Neural Network Based On the Improved Genetic Algorithm to Optimize Component Separation Conditions of Small Peptide

Abstract:

Reference to traditional optimization methods, neural network based on improved genetic algorithm is used in optimization of reversed phase chromatography pluralistic isocratic mobile phase separation conditions. With detailing the combination of the improved genetic algorithm and neural network theory, the optimization process for the liquid chromatography conditions is introduced in details. Used this method to small peptide RP chromatography optimization, after searching operation, the establishment of an effective separation of forecast model receives satisfactory predictive value, which can prove that this method can be used in optimization of drug liquid chromatography conditions.

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Periodical:

Advanced Materials Research (Volumes 284-286)

Pages:

261-264

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.284-286.261

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Online since:

July 2011

Authors:

Jing Wen Tian, Feng Jun Wu, Hui Chen, Jing Di Ren

Keywords:

Genetic Algorithm (GA), High Performance Liquid Chromatography (HPLC), Neural Network (NN), Optimization of Separation Conditions

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