Optimization method of microbial fermentation control based on memetic algorithm

Abstract

The invention discloses a method for optimizing microbial fermentation control based on a Memetic algorithm, which comprises the following steps: establishing a microbial fermentation data set, constructing a BP neural network, using the training data set to train the BP neural network, and controlling parameters for microbial fermentation Binary coding, execution of crossover operator, execution of local search operator by hill-climbing algorithm, execution of mutation operator, execution of local search operator again, the selected better individual as the current solution, and the qualified BP neural network trained in step 4 As a fitness function, calculate the fitness value of each individual in the population, and then update the population through the selection operator, find the optimal individual from the new population, and record the optimal combination of control parameters. The present invention can acquire the optimal control parameter combination according to the existing fermentation data without redesigning the experiment.

Description

technical field [0001] The invention relates to the field of microbial fermentation, in particular to a method for optimizing microbial fermentation control based on a Memetic 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 and optimize t...

AI Technical Summary

Problems solved by technology

[0007] In order to solve the above-mentioned technical problems, the present invention provides a microbial fermentation control optimization method based on the Memetic algorithm, which is used to solve the problem that the existing microbial fermentation control process requires pre-designed experiments, and it is difficult to obtain the optimal individual for fermentation, so as to improve the search rate of individual fermentation and convergence

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