【摘要】 根据Kohonen自组织特征映射神经网络中学习阶段的性质,对标准Kohonen神经网络进行了改进,通过选取不同的学习率和邻域函数,将学习阶段分为粗调整学习和微调整学习二个阶段,使Kohonen神经网络的训练速度和收敛效果有一定程度的提高,改善了聚类效果。同时在Kohonen神经网络的输出层添加一模糊聚类层,为挖掘用户的多种兴趣提供了一种可行的方法。更多还原

【Abstract】 According to the Kohonen self-organizing feature map neural network in the nature of the learning stage,the studying will be divided into two stages by choosing a different learning rate and neighborhood function: rough adjustment studying and micro-adjustment studying.It leads to improve the results from Kohonen Neural network convergence and the clustering accuracy,and provides a workable solution for a variety of users interesting in customers mining.更多还原