Rule based systems and networks: deterministic and fuzzy approaches

Han Liu; Alexander Emilov Gegov

doi:10.1109/IS.2016.7737440

Rule based systems and networks: deterministic and fuzzy approaches

Han Liu, Alexander Emilov Gegov

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

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.

Original language	English
Title of host publication	Proceedings of the 8th IEEE International Conference on Intelligent Systems
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	316-321
Number of pages	6
ISBN (Electronic)	978-1509013548
ISBN (Print)	978-1509013555
DOIs	https://doi.org/10.1109/IS.2016.7737440
Publication status	Published - 10 Nov 2016
Event	2016 IEEE International Conference on Intelligent Systems - Sofia, Bulgaria Duration: 4 Sept 2016 → 6 Sept 2016 Conference number: 8

Conference

Conference	2016 IEEE International Conference on Intelligent Systems
Abbreviated title	IS'16
Country/Territory	Bulgaria
City	Sofia
Period	4/09/16 → 6/09/16

Keywords

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

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Cite this

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title = "Rule based systems and networks: deterministic and fuzzy approaches",

abstract = "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.",

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AB - 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.

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KW - rule based networks

KW - data mining

KW - machine learning

KW - rule learning

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PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 4 September 2016 through 6 September 2016

ER -

Rule based systems and networks: deterministic and fuzzy approaches

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Keywords

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