Chemical Process Modeling Of Kidney-Inspired Algorithm

The kidney-inspired algorithm is an intelligent algorithm inspired by the functions of human kidney.Based on the research on the performance of kidney-inspired algorithm,this thesis studies the improvement of kidney-inspired algorithm.The main contents of this thesis are as follows:(1)The thesis briefly introduces the generation and principle of kidney-inspired algorithm,and combined with the optimization results of the classical test function,the convergence curve and the population distribution map to evaluate the performance of the algorithm.Based on this,the deficiency of kidney-inspired algorithm is summarized.(2)In view of the insufficiency of the kidney-inspired algorithm,the thesis is inspired by the particle swarm optimization algorithm to improve the motion equation of the kidney-inspired algorithm.In order to further enhance the local search accuracy of the algorithm,the molecular operation is introduced.The evaluation of the optimization results of typical test functions with the other two optimization algorithms shows that the performance of the kidney algorithm inspired by the particle swarm optimization algorithm behaves best.In addition,this thesis introduces the Caputo gradient descent algorithm,which has better search accuracy than the traditional gradient descent algorithm.In order to establish an accurate model of the gasoline pipeline blending process,this thesis combines kidney algorithm inspired by the particle swarm optimization algorithm and the Caputo gradient descent algorithm to optimize an improved RBF.Compared with the empirical method RBF and K-means RBF modeling,the result of the improved RBF network has a higher precision.(3)In order to improve the performance of the Kidney-inspired algorithm,this thesis redefines the filtering function and the motion equation,and introduces the Levy flight,and proposes an improved Kidney-inspired algorithm.In the objective evaluation with the other three optimization algorithms,the performance of the improved Kidney-inspired algorithm is best.In order to establish an accurate model of the FCCU Reaction-Regeneration System,this thesis combines the improved Kidney-inspired algorithm and the Caputo gradient descent algorithm to propose an improved diagonal recurrent neural network to model the FCCU Reaction-Regeneration System.In the comparison experiment with the identification results of DRNN,the improved DRNN algorithm has a higher precision.