Parameter Estimation Method for Nonlinear Model Based on Improved Fruit Fly Optimization Algorithm
Abstract Based on deep analysis of the optimization process of the basic fruit fly optimization algorithm, this paper supports an improved fruit fly optimization algorithm (IFOA) for search processing of a single direction. The IFOA method can process the nonlinear function that has nonzero and nonnegative extreme points. Based on this advantage, IFOA method is applied to parameter estimation of a nonlinear model. Analysis results of a practical example show that estimation accuracy of the IFOA method is superior to the linear approximation method and the nonlinear iterative method. Compared with intelligent search methods represented by a genetic algorithm, estimation accuracy is nearly equal. In addition, the IFOA method has several obvious advantages, including fewer parameter settings, ease of finding the best one, and easy programming.
Key words :
fruit fly optimization algorithm
search processing for single direction
nonlinear model; 
parameter estimation
intelligent search method
Cite this article:
FAN Qian. Parameter Estimation Method for Nonlinear Model Based on Improved Fruit Fly Optimization Algorithm[J]. jgg, 2016, 36(12): 1092-1096.
FAN Qian. Parameter Estimation Method for Nonlinear Model Based on Improved Fruit Fly Optimization Algorithm[J]. jgg, 2016, 36(12): 1092-1096.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2016/V36/I12/1092
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