Based on this, we proposed the Fuzzy Support Vector Machines (FSVM).
在此基础上，构造模糊支持向量机(算法)。
In order to improve the training efficiency, an advanced Fuzzy Support Vector Machine (FSVM) algorithm based on the density clustering (DBSCAN) is proposed.
为了提高模糊支持向量机在数据集上的训练效率，提出一种改进的基于密度聚类(DBSCAN)的模糊支持向量机算法。
The adaptive parameter optimization algorithm is applied to dynamically search the parameters of FSVM(Fuzzy Support Vector Machine) to enhance the convergence speed.
为提升算法的收敛速度，采用参数自适应优化算法动态搜索模糊支持向量机的模型参数。
The simulation results on UCI show that NFS-RSVM can remove most of the noises effectively, and the accuracy is improved partly compared with the traditional SVM and FSVM.
基于UCI数据集的仿真结果表明，NFS - RSVM方法能有效地将数据中的大部分噪声点去除，与传统的SVM和FSVM相比分类精度有一定程度的提高。
Based on clustering FSVM and current injection method, a new method using two steps for single-phase grounding fault location of distribution feeders in networks with ungrounded neutral is proposed.
提出小电流接地系统实现单相接地故障定位的新方法。该方法应用基于聚类的FSVM和电流注入法分两步实现故障定位。
Based on clustering FSVM and current injection method, a new method using two steps for single-phase grounding fault location of distribution feeders in networks with ungrounded neutral is proposed.
提出小电流接地系统实现单相接地故障定位的新方法。该方法应用基于聚类的FSVM和电流注入法分两步实现故障定位。
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