改进的蝴蝶优化聚类算法

针对当前算法在求解聚类问题时存在精度低、速度慢及鲁棒性差等问题，提出一种改进的蝴蝶优化聚类算法，借鉴精英策略思想重新定义蝴蝶优化算法的局部搜索迭代公式，然后融合遗传算法的选择、交叉和变异操作.在1个人工数据集和5个UCI数据集上的测试结果表明所提出算法的性能，且与其他算法相比具有一定优势.

Improved Butterfly Optimization Algorithm for Clustering

Aiming at the problems of low accuracy, slow speed, and poor robustness of the current algorithm in solving the clustering problem, an improved butterfly optimization clustering algorithm was proposed. Based on the idea of elite strategy, the local search iterative formula of butterfly optimization algorithm was redefined, and then the selection, crossover, and mutation operations of genetic algorithm were fused. Test results on one artificial dataset and five UCI datasets demonstrate that the performance of the proposed algorithm is superior to other algorithms.