电子学报Issue(8)：1555-1559,5.DOI:10.3969/j.issn.0372-2112.2013.08.016
自适应粒子群优化算法及其在测试数据生成中的应用研究
Adaptive Particle Swarm Optimization Algorithm and Its Application in Test Data Generation
摘要
Abstract
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 .关键词
粒子群算法/测试数据自动生成/进化方程约简/惯性权重/自适应调整方案/粒子聚集度Key words
particle swarm algorithm/automatic test data generation/reduce the evolution equation/inertia weight/adaptive adjustment scheme/particle aggregation degree分类
信息技术与安全科学引用本文复制引用
史娇娇,姜淑娟,韩寒,王令赛..自适应粒子群优化算法及其在测试数据生成中的应用研究[J].电子学报,2013,(8):1555-1559,5.基金项目
国家自然科学基金（No ．60970032）；江苏省“青蓝工程” （）
