1) weight adjustment
权值调整
1.
Based on this,an approach of term weight adjustment is proposed.
据此,提出一种特征项的权值调整策略,实验结果验证了该方法的有效性。
2.
The new model was based on the weight adjustments of error back propagation of BP algorithm and the weight modification using particle swarm optimization(PSO).
提出一种基于粒子群算法优化BP网络的权值调整新方法。
3.
Simultaneously it also considers the effects of similar features in similarity computation and weight adjustment to agglomerate documents with semantic similarities,and dynamically adjusts weights of documents to make unbalanced documents well trained.
本文提出一种有效处理高维数据的聚类算法,算法首先通过构造特征链将文档集合划分为多个类别,同时在相似度计算及权值调整时考虑相似特征的影响以凝聚语义相似的文档,并动态调整文档权重使分布不平衡的文档得到充分训练。
2) Weight self-tuning
权值自调整
1.
Introduced a new method to construct Design and Implementation of Weight self-tuning fuzzy PI control in DC motor Control System based on DSP2407.
针对直流电动机控制,介绍了一种基于TMS320LF2407DSP芯片的权值自调整模糊控制器和软硬件设计方法。
3) Bi-phases Weights Adjusting(BPWA)
双向权值调整
4) Weights Adjusting
自适应权值调整
1.
Weights Adjusting C-V Model and Image Segmentation;
自适应权值调整的C-V模型及图像分割
5) Training documents weight-adjusting
调整训练文本权值
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参考词条