学习向量量化 meaning in Chinese

lvq learning vector quantization

When the number of the training samples were on the two numbers , 200 and 250 , the classified accuracy was irregular , and the difference between these two number was not significant
在实验设计上，先产生三种混合样本资料，以比较在各种不同的实验设计下，学习向量量化网路分类正确性之差异。
The purpose of this study was to explore the effect of the different training samples , learning rate and numbers of hidden layers on the classified accuracy when using learning vector quantization to analysis
摘要本研究采电脑模拟探讨不同训练范例样本数、学习速率及隐藏层个数对学习向量量化网路分类正确率之影响。
Collecting and reading the correlative reference documents all over the world ; based on analyzing the performances and characteristics of neural network , employing the learning vector quantification neural network to recognize the flow regime of gas - solid two - phase flow , and carrying out simulation research
阅读国内外有关参考文献，在分析研究神经网络的功能及特点的基础上，选取学习向量量化神经网络作为气固两相流流型辨识的手段，并进行了仿真研究。