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用于人脸识别的主成分分析和模糊支持向量机程序，通过测试，能完成工作,Face Recognition for the principal component analysis and fuzzy support vector machine procedures, to pass the test to complete the work
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用于人脸识别的模糊独立成分分析+主成分分析，用模糊支持向量机进行的分类。,Fuzzy Face Recognition for independent component analysis+ principal component analysis, using fuzzy support vector machine classification.
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首先用PCA对ORA人脸图像降维，然后用模糊支持向量机对提取的特征向量进行分类，识别率较高。-First using PCA for dimensionality reduction ORA face image, and then use fuzzy support vector machine to classify the extracted feature vectors, the recognition rate is higher.
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：对每一个训练点都定义点模糊度，利用其隶属函数所包含的信息量来确定模糊度，在
此基础上对传统的支持向量机算法进行了改进，提出了基于模糊支持向量机的医学图像分类
技术。-: For each training point of ambiguity points are defined using the membership function to determine the amount of information contained ambiguity, on the basis o
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Predicting the longitudinal dispersion coefficient using support vector machine and adaptive neuro-fuzzy inference system techniques
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