阐述了模糊支持向量机的原理。
在此基础上，构造模糊支持向量机(算法)。
Based on this, we proposed the Fuzzy Support Vector Machines (FSVM).
采用模糊支持向量机对某型飞机飞行动作进行识别。
Six kinds of recorded flight data of flight action are recognized by FSVMs.
针对飞行动作识别提出解决这一现象的模糊支持向量机。
Flight action recognition is proposed in this paper based on the fuzzy support vector Machines (FSVMs).
实验结果显示，采用模糊支持向量机有效地提高了识别准确度。
The experiments show using fuzzy support vector machine significantly improves the overall recognition rate.
将其应用于模糊支持向量机方法中，较好地将支持向量与含噪声或野值样本区分开。
The fuzzy membership based on the affinity among samples for support vector machine effectively distinguishes between support vectors and outliers or noises.
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 adaptive parameter optimization algorithm is applied to dynamically search the parameters of FSVM(Fuzzy Support Vector Machine) to enhance the convergence speed.
仿真试验结果表明这种新的模糊支持向量机方法不但有较高的分类准确率，而且对隶属度有很强的预测能力。
Emulational experimental result shows that this new fuzzy support vector machine method not only has higher classified accuracy, but also has stronger test capability for the membership degree.
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。
In order to improve the training efficiency, an advanced Fuzzy Support Vector Machine (FSVM) algorithm based on the density clustering (DBSCAN) is proposed.
提出了基于损失函数的模糊判决支持向量机算法，并与模糊样本支持向量机算法进行了比较。
The fuzzy judgment support vector machine algorithm based on loss function is proposed, and compared with fuzzy sample support vector machine algorithm.
仿真研究表明，SVM具有优良的逆模型辨识能力，基于模糊控制补偿的支持向量机逆控制系统的动态性能好、跟踪精度高、鲁棒稳定性强。
Simulations demonstrate that SVM has good nonlinear approximation capability for inverse model, and the proposed control system has good dynamic and static performances as well as good robustness.
提出支持向量机-模糊预测控制方法，介绍支持向量机在列车启动控制过程中的应用。
It is proposed a fuzzy forecast control method based on support vector machine. The applications of the machine to the train start-up control are given.
论文研究模糊支持向量分类机在冠心病诊断中的应用。
In this paper, we have studied on applying fuzzy support vector classification to coronary heart diagnose.
给出带有模糊决策的模糊机会约束规划模型，在此基础上，研究模糊线性支持向量分类机(算法)和模糊线性支持向量回归机(算法)。
Proposed the model of fuzzy chance constrained programming with fuzzy decision, and did some research on fuzzy linear support vector regression (algorithm) on this base.
应用模糊理论的方法对支持向量机分类及最优分类面进行了解释，对可疑分类区列出了模糊隶属度的表达式。
A method based on fuzzy theory is applied to explain the classification of SVM and its optimal hyperplane. An expression of fuzzy membership on doubtful classification area is listed.
该方法基于半模糊核聚类算法挖掘不同类别之间的衔接和离散信息，设计树型支持向量机的树型结构，克服其差错积累问题。
The method mines information on overlap between classes, designs the tree structure and overcomes the misclassification of tree-structured SVMs based on the semi-fuzzy kernel clustering algorithm.
学习过程分为离线学习支持向量机和在线整定模糊比例因子两部分。
And its learning procedure includes two parts: offline training of SVM and online training of fuzzy scale factors.
研究基于模糊系数规划的模糊支持向量分类机。
Research on the fuzzy SVMs based on fuzzy coefficient programming.
并将新的模糊隶属度模型引入自适应支持向量机，提出了模糊自适应支持向量机算法。
Introducing the novel fuzzy membership model into Adaptive Support Vector Machine (ASVM), we propose an Adaptive fuzzy Support Vector Machine algorithm (AFSVM).
针对图像在获取和传输过程中易受各种噪声污染的事实，为了提高支持向量机对噪声图像的分割性能，提出了模糊权重支持向量机。
In order to improve the segmentation performance of images corrupted by impulse noise and Gaussian noise, fuzzy weighted support vector machine is proposed.
梯形模糊数样本是一类非随机样本，本文将讨论基于梯形模糊数样本的支持向量机。
The trapezoidal fuzzy number sample is one of non-real random samples. This dissertation will discuss the support vector machine base on trapezoidal fuzzy numbers.
梯形模糊数样本是一类非随机样本，本文将讨论基于梯形模糊数样本的支持向量机。
The trapezoidal fuzzy number sample is one of non-real random samples. This dissertation will discuss the support vector machine base on trapezoidal fuzzy numbers.
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