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基于模糊神经网络的四象体质分类的2-D可视化模型

A 2-D Visual Model for Sasang Constitution Classification Based on a Fuzzy Neural Network

作者:Zhen-Xing ZhangXue-Wei TianJoon S. Lim 加工时间:2014-09-22 信息来源:科技报告(Other) 索取原文[6 页]
关键词:EUM;电气工程;模糊神经网络
摘 要:The human constitution can be classified into four possible constitutions according to an individual's temperament and nature: Tae-Yang (太陽), So-Yang (少陽), Tae-Eum (太陰), and So-Eum (少陰). This classification is known as the Sasang constitution. In this study, we classified the four types of Sasang constitutions by measuring twelve sets of meridian energy signals with a Ryodoraku device (良導絡). We then developed a Sasang constitution classification method based on a fuzzy neural network (FNN) and a two-dimensional (2-D) visual model. We obtained meridian energy signals from 35 subjects for the So-Yang, Tae-Eum, and So-Eum constitutions. A FNN was used to obtain defuzzification values for the 2-D visual model, which was then applied to the classification of these three Sasang constitutions. Finally, we achieved a Sasang constitution recognition rate of 89.4.
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