基于人工蜂群算法的超声回波参数估计  

Artificial bee colony algorithm for parameter estimation of ultrasonic echo

作　　者：周京华[1] 张小凤[1] 张光斌[1] 

机构地区：[1]陕西师范大学物理学与信息技术学院陕西省超声学重点实验室,西安710062

出　　处：《计算机工程与应用》2014年第14期189-193,共5页Computer Engineering and Applications

基　　金：陕西省自然科学基金(No.2012JM1013);西安市科技计划项目(No.CXY1206(7));中央高校基本科研业务费专项资金资助(No.GK201102026)

摘　　要：将适用于求解组合优化问题和连续优化问题的人工蜂群算法运用于超声回波的非线性高斯模型,提出了一种基于人工蜂群算法的超声回波参数估计新方法,给出了算法的基本步骤,并在不同初始条件下对算法的性能进行了仿真。仿真结果表明,该算法的估计精度与初始值的选择无关,不仅能成功估计出超声回波模型的各个参数,而且可在全局范围内取得最优解,与超声回波参数估计的蚂蚁算法相比,该算法具有收敛速度快,运行时间短,鲁棒性好,可进行实时处理的优点。This paper proposes a parameter estimation method for nonlinear Gaussian model of ultrasonic echo based on artificial bee colony algorithm, which is applied to solve combinatorial optimization problems and continuous optimiza-tion problems. It gives the basic steps of the algorithm, and simulates the performance of the algorithm in different initial conditions. Simulation results show that, the estimation accuracy of the algorithm is independent of the initial value selec-tion. And it not only can successfully estimate the various parameters of the ultrasonic echo, but also can achieve the opti-mal solution in the global scope. Compared with ant colony optimization that applied to ultrasonic echo parameter estima-tion, the algorithm has the advantages of fast convergence speed, short running time, robustness, real-time processing.

关 键 词：人工蜂群算法 群体智能 全局优化 超声回波 超声检测 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TN912.16[自动化与计算机技术—控制科学与工程]