A Rule-Based Inference Method Using Dempster-Shafer Theory

被引：2
|
作者：
Jin, Liuqian [1 ]
Xu, Yang [2 ]
机构：
[1] Southwest Jiaotong Univ, Intelligent Control Dev Ctr, Chengdu 610031, Peoples R China
[2] Southwest Jiaotong Univ, Sch Econ & Management, Chengdu 610031, Peoples R China
来源：
KNOWLEDGE ENGINEERING AND MANAGEMENT , ISKE 2013 | 2014年 / 278卷
基金：
美国国家科学基金会;
关键词：
Uncertainty reasoning; Dempster-Shafer theory; Knowledge representation; Rule-base; Interval number; EVIDENTIAL REASONING APPROACH;
D O I：
10.1007/978-3-642-54930-4_7
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The Dempster-Shafer theory of evidence for attribute aggregation provides a method to deal with uncertainty reasoning. In this paper, uncertainty reasoning method based on rule-base with certainty interval is investigated. First, knowledge representation with interval uncertainty is defined and the matching principle is given. Then, a rule-based inference method under interval numbers using Dempster-Shafer theory is derived. A numerical example is examined to show the implementation process of the proposed method.
引用
收藏
页码：61 / 72
页数：12
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