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.