Back-propagation (BP) neural network immune genetic algorithm based microbial fermentation optimization method

Abstract

The present invention discloses a back-propagation (BP) neural network immune genetic algorithm based microbial fermentation optimization method which is characterized by comprising the following steps: establishing a microbial fermentation dataset, constructing a BP neural network, using the training dataset to train the BP neural network, performing binary coding on microbial fermentation control parameters, executing a vaccine extraction operator on an initial population, executing a crossover operator, executing a mutation operator, executing a vaccine inoculation operator, taking the BP neural network that is qualified in the training in step four as a fitness function to calculate the fitness value of each individual in the population, executing an immune detection operator, calculating the concentrations of the individuals, executing an immunologic balance operator, and finding optimum individuals from a new population generated by fermentation. The BP neural network immune genetic algorithm based microbial fermentation optimization method can be used for obtaining an optimum control parameter combination according to the existing fermentation data, and the redesign an experiment is not needed.

Description

technical field [0001] The invention relates to the field of microbial fermentation, in particular to a method for optimizing microbial fermentation based on BP neural network immune genetic algorithm. Background technique [0002] The microbial fermentation process is a highly complex and nonlinear process, and it is difficult to model the fermentation process with an accurate mathematical model. In recent years, with the development of computational intelligence algorithms, more and more computational intelligence algorithms have been applied to the modeling and optimization control of microbial fermentation processes. For example, BP neural network, genetic algorithm, etc. are used to model and optimize the fermentation process. In the prior art, the BP neural network and the genetic algorithm are often applied alone to the modeling and optimization control of the fermentation process. There is also a joint application of BP neural network and genetic algorithm to model...

AI Technical Summary

Problems solved by technology

[0007] In order to solve the above-mentioned technical problems, the present invention provides a microbial fermentation optimization method based on BP neural network immune genetic algorithm, which is used to solve the need to pre-design fermentation experiments in the existing microbial fermentation control process, and it is not easy to obtain the optimal fermentation individual and optimal fermentation. The question of control parameters

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