Chemical procedure modelling approach possessing reconstructed operation RNA genetic algorithm

Abstract

The invention discloses a chemical engineering process modeling method of an RNA genetic algorithm with remodeling operation, which has the following steps: 1) actual input and output sampling data is obtained by on-site operation or experiment, and then the sum of the absolute value of the error between the estimated output and the actual output of a chemical engineering process model is used asthe objective function of the RNA genetic algorithm for optimization research; 2) algorithm control parameters is set; 3) the RNA genetic algorithm with remodeling operation is operated to do estimation for the unknown parameters of the chemical engineering process model, then the estimated value of the unknown parameters of the chemical engineering process model is obtained by the minimized objective function, and the estimated value of the unknown parameters is substituted into the chemical engineering process model to form a mathematical model of the chemical engineering process. The excellent genes of original species group is preserved when the diversity of the species group is increased effectively, thereby avoiding the defects of the premature convergence of traditional genetic algorithm and the convergence of locally optimal solution better.

Description

technical field [0001] The invention relates to a chemical process modeling method of RNA genetic algorithm with reconstruction operation. Background technique [0002] The modeling and control of chemical process has always been one of the key research areas of enterprises and scientific research institutions. It is an indispensable link in the production of modern chemical industry, and modern industrial control is based on models, that is to say, the mathematics of chemical process Models are at the heart of control. According to the reaction mechanism of the chemical process, the researchers put forward the corresponding chemical process model structure. However, in these chemical process models with known model structures, there are many parameters that cannot be directly measured. It is necessary to use parameter estimation methods to estimate the values ​​of these unknown parameters, and substitute the estimated values ​​of these parameters into the corresponding che...

AI Technical Summary

Problems solved by technology

However, the research work on such algorithms is in its infancy, and there are still many problems to be solved.

For example, the optimization performance is poor in a high-dimensional environment; on highly deceptive problems, the model deception cannot be overcome, and it is easy to fall into a local optimal solution

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