A complex chemical process modeling method based on dna genetic algorithm based on bee colony behavior

Abstract

The invention discloses a complex chemical process modeling method of a DNA genetic algorithm based on a swarm behavior. The method includes the following steps of firstly, obtaining input sampling data and output sampling data in the chemical process through experiments, and using the sum of an error absolute value of estimated output of a model and an error absolute value of practical sampling output in the chemical process as a fitness function aiming at the input sampling data in the same chemical process; secondly, setting control parameters of the algorithm; thirdly, conducting estimation on unknown parameters in a chemical process model by running the algorithm, obtaining estimated values of the unknown parameters in the model through a minimum objective function value, putting the estimated values of the unknown parameters in the model into the chemical process model, and obtaining an optimal chemical process model. According to the complex chemical process modeling method of the DNA genetic algorithm based on the swarm behavior, by the adopting of the DNA genetic algorithm based on a swarm honey gathering behavior and a swarm breeding behavior, the established chemical process model is made to have high fitting precision, and has the advantages of being high in convergence rate and rich in population diversity.

Description

technical field [0001] The invention relates to a process modeling method, in particular to a complex chemical process modeling method based on the DNA genetic algorithm of bee colony behavior. Background technique [0002] With the scale and large-scale of chemical production, the requirements for chemical process control are constantly increasing, and the establishment of high-precision chemical process models is an important way to achieve effective control. The chemical process is nonlinear, time-delayed, some variables are unmeasurable, and the coupling between variables, etc., which makes the chemical process modeling become a research difficulty and hot spot. Inspired by the research results of biological science and technology, the optimization modeling method of chemical process based on biological computing has developed rapidly. Such as artificial neural network, genetic algorithm, ant colony algorithm, tabu search, etc. These biocomputation-based optimization a...

AI Technical Summary

Problems solved by technology

Among them, the genetic algorithm, as a random search method that is not strict on the problem and has a wide range of adaptability, has a strong global search ability, but the traditional genetic algorithm has the disadvantages of poor local search ability and premature convergence.

The DNA genetic algorithm effectively overcomes the shortcomings of the traditional genetic algorithm. Inspired by the bee colony breeding behavior and the bee colony honey harvesting behavior, the present invention proposes a complex chemical process modeling method based on the bee colony behavior DNA genetic algorithm, which can be used It is used to solve the optimization modeling problem of multi-variable and nonlinear complex chemical process

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