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MATLAB中应用支持向量肌（SVN）神经网络对模式识别处理-MATLAB Application of Support Vector muscle (SVN) neural network for pattern recognition processing
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能够实现支持向量机的界面操作，支持向量机比神经网络功能强大，能够实现分类和识别-Support vector machine (SVM) to realize the interface operation, support vector machine (SVM) is a powerful than neural network, which can achieve the classification and recognition
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SVM神经网络的数据分类预测——葡萄酒种类识别-SVM neural network data classification forecast- wine species identification
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SVM神经网络的数据分类预测-葡萄酒种类识别-SVM neural network data classification forecast- Wine Type Identification
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SVM神经网络的回归预测分析---上证开盘指数预测-SVM neural network regression analysis--- Shanghai opening index prediction
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MATLAB神经网络的各类程序，包含遗传算法，神经网络，神经模糊，SVM等程序，十分实用。-All kinds of MATLAB neural network program, including genetic algorithms, neural networks, neuro-fuzzy, SVM and other procedures, very useful.
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支持向量机神经网络的实例应用,可以正常运行-SVM neural network application examples
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The SVM neural network information graining time
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SVM neural network information granulation time series regression forecast
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SVM神经网络的数据分类预测-葡萄酒种类识别，能够很好地预测葡萄酒种类。-SVM neural network data classification prediction- wine species identification, can be a good predictor of wine types.
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