Abstract：The genetic algorithm is usually selected as an optimization tool for the least square fitting about ordered plane data by B-spline curves. But the result easily falls into the local optimum with random initial choice, and more control points are required to assure higher accuracy. The adaptive genetic algorithm was proposed to overcome the shortcoming during the parameter optimization for B-spline curves. The average fitness of the initial populations was improved obviously by the average data parameter value method, which built the relationship between the data parameters and the knots. In the algorithm, the evolution of populations was accelerated through the optimization for the genetic strategy. The experimental results show that the algorithm can do with minimum control points and better precision within lower iterations.
2010, Vol. 30 
