摘要
根据不等距节点原理,利用生物地理优化算法求解数值积分。介绍了生物地理优化算法的基本原理,定义了栖息地适应性指数、适合指数变量等参数,给出了迁移和变异操作的数学模型。根据数值积分不等距节点原理,在积分区间内任意选取一定的节点,采用生物地理优化算法优化这些节点求取积分值。最后,利用Matlab软件进行了仿真和实验,以证明该算法的有效性。典型的数值积分函数实例仿真表明,利用生物地理优化算法求解数值积分具有精度高和自适应强的特点,计算结果好于粒子群算法、梯形法和Simpson法。
Biogeography-based optimization（ BBO） was used to solve numerical integration. Firstly,the principle of BBO algorithm was introduced, habitat suitability index and suitability index variables were defined, and then mathematical model of migration and mutation operation was given. Secondly,BBO was used to optimize unequal node points in the integral interval,then a more precise integral result was obtained. Finally,simulation was carried out by Matlab software. The calculation results of typical numerical integral function showed that numerical integration method by BBO algorithm is better than those by PSO algorithm,trapezoidal method and Simpon method. The method is with the advantage of high precision and good adaptability.
出处
《实验室研究与探索》
CAS
北大核心
2014年第12期20-22,61,共4页
Research and Exploration In Laboratory
基金
国家自然科学基金(61262037)
四川省教育厅基金项目(13ZB0213)
关键词
生物地理优化算法
数值积分
粒子群算法
不等距节点
biogeography-based optimization
numerical integration
particle swarm optimization
unequal node points
