CAJ | 학술논문

针对粒子群算法易陷入局部最优解及搜索精度低的问题，本文提出一种约简的自适应粒子群优化算法并应用于测试数据的自动生成。首先对粒子群进化方程约简，提出无速度项的粒子群进化方程；然后，对约简后的方程提出基于惯性权重的自适应调整方案，将惯性权重直接作用于粒子的位置，并根据粒子的适应度及聚集度将种群划分为三部分。实验表明，该方法可以有效地提高自动生成测试数据的效率。
침대입자군산법역함입국부최우해급수색정도저적문제，본문제출일충약간적자괄응입자군우화산법병응용우측시수거적자동생성。수선대입자군진화방정약간，제출무속도항적입자군진화방정；연후，대약간후적방정제출기우관성권중적자괄응조정방안，장관성권중직접작용우입자적위치，병근거입자적괄응도급취집도장충군화분위삼부분。실험표명，해방법가이유효지제고자동생성측시수거적효솔。
According to the particle swarm algorithm that easily falls into the local optimal solution and the problem of low search accuracy ,this paper proposes reduced adaptive particle swarm optimization algorithm for generating test data automatically . First ,this paper reduces the evolution equations of particle swarm and presents evolution equations without velocity .Then this paper proposes adaptive adjustment scheme based on inertia weight and inertia weight is directly acted on the particle position .According to the particle fitness and particle aggregation degree ,the population will be divided into three parts .The experiments show that our approach can effectively improve the efficiency of generating test data automatically .