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模糊支持向量机文档，将模糊理论与支持向量机相结合-FSVM documents, the fuzzy theory and support vector machines combine
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利用支持向量机对T-S型模糊系统建模的方法，结合BP算法对参数进行优化，从一定程度上解决模糊系统建模所存在的模型结构复杂、维数灾、泛化能力不强和实时性差等问题。-this paper analyzed the approach that applied support vector machines to create novel model in the T-S fuzzy system, combined with BP algorithm which could optimize it,
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模糊——支持向量机，用于模糊理论与支持向量机结合，用于数据预测-Fuzzy- support vector machines for fuzzy theory and support vector machines for data predict
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this is a good paper about fuzzy SVM
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支持向量机模型研究及应用，本文所做的工作主要在如下几个方面：
1)运用模糊集理论(FST)和概率理论对支持向量机进行研究，构造出了概率模糊支
持向量机(PFSVM)模型，既达到了减少或者消除外围异样点对于整个训练模型的影响，-Support vector machine model and application, this work mainly in the following aspects: 1) the use of fuzzy set theory (FST) and the
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基于局部能量与模糊逻辑的红外偏振图像融合，该文与小波包，支持向量机等融合算法进行对比分析，说明该文算法的优势。-Infrared polarization image fusion based on local energy and fuzzy logic, this paper, wavelet packet, support vector machines and other fusion algorithm comparison analysis to illustrate the adv
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涵盖目前识别和智能计算的理论和方法，包括支持向量机，神经网络，决策树，粗糙集理论，模糊集理论，和遗传算法-Covers the recognition and intelligent computing theory and methods, including support vector machines, neural networks, decision trees, rough set theory, fuzzy set theory and genetic algorithm
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describing FSVM.learns the decision surface two distinct classes of the input points.In many applications,each input point may not be fully assigned to one of these two classes. In this paper, we apply a fuzzy membership to each input point and refor
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对目标函数的松弛变量引入一个参数μ，优化基本的最小二乘一类支持向量机算法。同样是解决线性问题，避免了二次规划的复杂问题(A parameter min is introduced into the relaxation variable of the objective function, and the basic least squares support vector machines algorithm is optimized. It also solves the linear pr
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