CAJ | 학술논문

将自然生态系统中生物生命周期的思想引入二元蚁群优化算法中，通过对蚂蚁设置相应的营养阈值而执行繁殖、迁徙、死亡操作，从而保持种群的动态多样性，进而克服二元蚁群优化算法易陷入局部最优的缺陷，然后结合分形维数将该算法应用于属性约简问题中，通过UCI中的6个数据集进行测试，结果表明该算法具有较好的可行性和有效性。
장자연생태계통중생물생명주기적사상인입이원의군우화산법중，통과대마의설치상응적영양역치이집행번식、천사、사망조작，종이보지충군적동태다양성，진이극복이원의군우화산법역함입국부최우적결함，연후결합분형유수장해산법응용우속성약간문제중，통과UCI중적6개수거집진행측시，결과표명해산법구유교호적가행성화유효성。
The biological life cycle in natural ecosystem is introduced into binary ant colony optimization algorithm, and the main idea is to execute breeding, migrating and dying operations by setting relevant nutritious threshold value to the ants. Thus, the dynamic diversity of the population is maintained and the drawback that binary ant colony optimization algorithm easily traps in local optimum is overcome. The proposed algorithm, lifecycle-based binary ant colony optimization algorithm ( LCBBACO) , is combined with fractal dimension to attribute reduction problem. The experimental results on 6 UCI datasets show that the method has preferable feasibility and effectiveness.