关键词： 灰狼优化算法, 模糊C均值聚类算法, 读者借阅行为分析

Abstract:

This paper proposes a reader behavior analysis algorithm based on a gray wolf optimization clustering algorithm through analyzing the advantages and disadvantages of current reader behavior analysis algorithms at home and abroad. First, the gray wolf optimization algorithm automatically optimizes to find the optimal initial cluster center point of the fuzzy C-means clustering algorithm. It then makes an iterative calculation of the initial cluster center point to obtain the final clustering result. Through the analysis of the reader borrowing behavior data, it is verified that the gray wolf optimization clustering algorithm is superior to the ordinary clustering algorithm.

Key words: grey wolf optimization algorithm, fuzzy C-means clustering algorithm, reader behavior analysis