The Intelligent Optimization Algorithm With Derivatives To Solve Hydrological And Water Quality Parameters Optimization Problem

Intelligent optimization algorithm is an optimization algorithm by simulating or revealing certain natural phenomena or processes.Because of its simple operation and low requirement for objective function,it has been widely used in solving complex problems.However,the intelligent optimization algorithm has strong ability of global convergence and poor ability of local convergence.The current emphasis is on improving its ability of local convergence.The common improvement method is to combine two intelligent optimization algorithms or combine the traditional optimization algorithm with the intelligent optimization algorithm,while the traditional optimization algorithm contains two classes,one contains derivatives and the other does not need guidance.The traditional optimization algorithm with derivative is faster than the traditional optimization algorithm without derivative.Considering the gradient descent method has simple operation and strong ability of local convergence,the gradient is added to the operation process of the intelligent optimization algorithm,formed the intelligent optimization algorithm with derivative,and it is applied to the hydro-geological parameters and the river water quality parameters solving process.The main research work is as follows:In this paper,it first introduces the basic theory,concrete operation steps and the program flow chart of several algorithms used in this paper,analyzes the advantages and disadvantages of each algorithm,proposes the PSO with derivative and the GA with derivative,and verifies the hybrid algorithms with several test functions,explaining the feasibility of the intelligent algorithm with derivative.Secondly,using the intelligent optimization algorithm with derivative and the standard intelligent optimization algorithm to solve the hydro-geological parameters and the water quality parameter.By comparing and analyzing the results,the feasibility of the intelligent optimization algorithm with derivative is verified to solve the problem of hydrology and water quality,and the calculated data obtained from the result are compared with the actual data,and the fitting degree is better,and the reliability of the results of the intelligent energy optimization algorithm containing the derivative is verified.Secondly,by comparing the computational process of the intelligent optimization algorithm with derivative and theintelligent optimization algorithm without derivative,it is found that the evolution times of the intelligent optimization algorithm with derivative are obviously less than the intelligent optimization algorithm without derivative,which fully shows that the rate of convergence for the intelligent optimization algorithm with derivative is faster.Finally,a slight disturbance is added to the original data,and the intelligent optimization algorithm with derivatives and the intelligent optimization algorithm without derivative are used again.It is found that the intelligent optimization algorithm with derivatives can still get the optimal solution quickly,and the operation process is relatively stable,and further verifies the intelligent optimization algorithm with derivative is not only more astringency but also more stable.