关键词: 历史疫灾分级, 聚类, 蚂蚁算法, 模拟退火算法

Abstract: Aiming at the problems of low quantization degree and strong social relevance in historical epidemic records, a historical epidemic classification method which based on simulated annealing and ant colony optimization is proposed in this paper. It uses a single ant to automatically generate the clustering result of epidemic data, and uses simulated annealing algorithm to optimize the clustering criteria, so as to obtain the global optimal solution of the epidemic clustering. In comparison with other clustering algorithms in performance, experimental results show that the proposed method has high accuracy and practicality.

Key words: historical epidemic classification, clustering, ant colony optimization, simulated annealing