基于相似度的三角模糊数Fisher线性判别分析  

Similarity-based Fisher Linear Discriminant Analysis for Triangular Fuzzy Number

作　　者：黄雅楠 魏立力 HUANG Ya＇nan,WEI Lili(School of Mathematical and Statistics, Ningxia University, Yinchuan750021, Chin)

机构地区：[1]宁夏大学数学统计学院,银川750021

出　　处：《计算机工程》2018年第8期38-42,47,共6页Computer Engineering

基　　金：国家自然科学基金(11261044)

摘　　要：针对三角模糊数的分类问题,构建基于相似性度量的Fisher线性判别分析模型。该模型是经典Fisher线性判别分析模型的推广,其利用三角模糊数的相似度刻画类内离散程度,根据三角模糊数的距离量化类与类之间的离散程度,同时寻找一个方向向量,使投影到该向量模糊数据的类间离散程度与类内离散程度之比最大。实例分析结果表明,该分类模型在胃病诊断方面具有有效性和适用性。For the classification problem of the triangular fuzzy number,this paper constructs similarity-based Fisher linear discriminant analysis model. The model is the generalization of the classical Fisher linear discriminant analysis model. The similarity of triangular fuzzy number is employed for discrete degree within class,with a distance of triangular fuzzy number to quantify between each class of dispersion degree. At the same time,an idea consists of finding a projection direction vector which maximizes the radio of the dispersion degree between the class data and within the class is proposed. The results of instance analysis show that the proposed classification model is effective and applicable in the diagnosis of gastric diseases.

关 键 词：FISHER线性判别分析 三角模糊数 相似度 离散程度 分类 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]