模糊聚类是目前知识发现（ＫＤＤ）领域中的研究分支之一，而神经网络是用于聚类的良好工具。将模糊理论引入到一种自适应的ＬＶＱ神经网络，提出了一种改进的模糊学习矢量化（ＦＬＶＱ）神经网络。模拟仿真与分析表明，该网络同传统ＬＶＱ神经网络相比，具有良好的聚类效果。 Fuzzy clustering is one of the research branches in the field of knowledge discovery (KDD), and neural network is a good tool for clustering. The fuzzy theory is introduced into an adaptive LVQ neural network, and an improved fuzzy learning vector (FLVQ) neural network is proposed. Simulation and analysis show that this network has good clustering effect compared with the traditional LVQ neural network.