算子优化遗传算法的插画艺术设计模型

发布时间：2018-02-28 12:01

本文关键词： K-GA算法插画艺术艺术设计算子优化聚类优化　出处：《科技通报》2017年08期 　论文类型：期刊论文

【摘要】：针对标准遗传算法在插画艺术设计的应用中还存在搜索效率低下、复杂度过高等问题。本文提出了一种基于算子及聚类优化遗传算法的插画艺术设计模型。首先在遗传算法运行中依据种群的特点来动态调整交叉概率和变异概率的数值,以提高算法的搜索效率,然后引入K-medoids算法对遗传算法进行聚类优化,并采用一个成本函数来进行评估聚类质量的好坏,以优化原算法的复杂度,最后采用改进遗传算法对随机插画艺术设计。通过实例仿真表明,本文提出的改进算法对插画艺术设计的实现,艺术性和创新性更高。
[Abstract]:In view of the low efficiency of searching in the application of standard genetic algorithm in illustration art design, In this paper, a design model of illustration art based on operator and clustering optimization genetic algorithm is proposed. Firstly, the crossover probability and mutation probability are dynamically adjusted according to the characteristics of population in the running of genetic algorithm. In order to improve the search efficiency of the algorithm, K-medoids algorithm is introduced to optimize the clustering of genetic algorithm, and a cost function is used to evaluate the quality of the clustering, so as to optimize the complexity of the original algorithm. Finally, an improved genetic algorithm is used to design the random illustration art. The simulation results show that the proposed improved algorithm is more artistic and innovative in the realization of the illustration art design.
【作者单位】：九江职业技术学院信息工程学院;温州大学图书馆;
【基金】：2016年江西省高校人文社科立项课题(课题编号:YS161006)
【分类号】：J218.5;TP18

【相似文献】