Rule Based Systems and Networks: Deterministic and Fuzzy Approaches

被引：0

作者：

Liu, Han ^{[1
]}

Gegov, Alexander ^{[1
]}

机构：

[1] Univ Portsmouth, Sch Comp, Portsmouth, Hants, England

来源：

2016 IEEE 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS (IS) | 2016年

关键词：

rule based systems; rule based networks; data mining; machine learning; rule learning; ensemble learning;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

a rule based system is a special type of expert system which consists of a set of rules. In practice, rule based systems can be built by using expert knowledge or learning from real data. Due to the vast and increasing size of data, the latter approach has become quite popular for building rule based systems. In particular, rule based systems can be built through use of rule learning algorithms, which can be based on statistical heuristics or random basis. This paper focuses on deterministic approaches for classification. This paper also features fuzzy approaches for modelling tasks. In general, this paper is mainly concerned with rule based systems that have a single rule base. However, some of the contents that relate to fuzzy approaches also include some concepts of multiple rule bases.

引用

页码：316 / 321

页数：6

共 27 条

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