Title :
Inverse Problem of Multiple Parameters Identification for BOD-DO Water Quality Model Using Evolutionary Algorithm
Author :
Xiang-Guo Liu ; Ke-Feng Ai
Author_Institution :
Math. Dept., Chaohu Coll., Chaohu, China
Abstract :
Parameter inversion of solute BOD-DO water quality model was generally solved through a nonlinear operator equation. The original problem is finally transformed into an optimization problem by creating fit function. We used the genetic algorithm, which can search the best solution from many initial points and obtain the total optimum solution of water quality model three parameters at the same time, and solve the problem by means of crossover and mutation operator. The results of numerical simulation show that the method has higher accuracy, quicker convergent speed and better stabilization than existing methods and is easy to program and calculate.
Keywords :
convergence; genetic algorithms; inverse problems; parameter estimation; water quality; convergent speed; crossover operator; evolutionary algorithm; fit function; genetic algorithm; inverse problem; multiple parameters identification; mutation operator; nonlinear operator equation; numerical simulation; optimization problem; parameter inversion; solute BOD-DO water quality model; stabilization; total optimum solution; Equations; Genetic algorithms; Inverse problems; Mathematical model; Parameter estimation; Water pollution; Water resources; genetic algorithm Introduction; parameter inversion; pollution; water quality model;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on
Conference_Location :
Shiyang
DOI :
10.1109/ICCIS.2013.286