计算机科学 ›› 2020, Vol. 47 ›› Issue (6A): 84-88.doi: 10.11896/JsJkx.190900148
张素梅1, 张波涛2
ZHANG Su-mei1 and ZHANG Bo-tao2
摘要: 提出了一种量子耗散粒子群算法,每个粒子信息位采用双本征态叠加表达,量子信息载体用于粒子群的种群差异化;并设计了惯性权重的自适应调整策略。针对4个经典测试函数进行了测试,结果表明所提算法相比标准粒子群、指数耗散粒子群和惯性递减耗散粒子群等算法具有明显的优势。将该算法用于一种教学评估模型的构建中,用于克服主观意识对客观评价的干扰,结果表明所建模型可以与现实数据高度拟合,取得了比人工经验模型更高的评估精度。
中图分类号:
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