This paper, based on the theory and method of artificial nerve networks and fuzzy sets, puts forward a classifier model used for diagnosing the quasi-heath state.
利用人工神经网络与模糊集的理论和方法提出了诊断亚健康状态的一种分类器模型。
For this object, a method of determining fuzzy integral density with membership matrix is proposed, and the classifier ensemble algorithm based on fuzzy integral is introduced.
给出了基于隶属度矩阵的模糊积分密度确定方法，介绍了基于模糊积分的分类器集成算法。
This fuzzy system design method that uses a fuzzy rule to represent a cluster is then propsed so that a fuzzy classifier can be efficiently constructed to correctly classify the training data.
用这样一个模糊规则来表示分类的模糊系统，更加有效地构建了一个能对训练样本比较准确分类的模糊分类器。
As a nonlinear method, the fuzzy rule-based pattern recognition has good comprehensibility, but has not been applied to the multiple classifier fusion.
而基于模糊规则的模式识别方法是一类可理解性好的非线性方法，但迄今为止还没有被应用于多分类器融合问题中。
As a nonlinear method, the fuzzy rule-based pattern recognition has good comprehensibility, but has not been applied to the multiple classifier fusion.
而基于模糊规则的模式识别方法是一类可理解性好的非线性方法，但迄今为止还没有被应用于多分类器融合问题中。
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