Advanced modelling of complex processes by rule-based networks

Alexander Gegov; Nedyalko Petrov; B. Vatchova

Advanced modelling of complex processes by rule-based networks

Alexander Gegov, Nedyalko Petrov, B. Vatchova

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

Abstract

This work presents an application of the novel theory of rule based networks for building models of processes characterised by uncertainty, non-linearity, modular structure and internal interactions. The application of the theory is demonstrated for a flotation process in the context of converting a multiple rule based system into an equivalent single rule based system by linguistic composition of the individual rule bases. During the conversion process, the transparency of the multiple rule based system is fully preserved while its accuracy is improved to a level comparable with the accuracy of the single rule based system.

Original language	English
Title of host publication	Intelligent Systems (IS), 2010 5th IEEE International Conference
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	197-202
Number of pages	6
ISBN (Print)	9781424451630
Publication status	Published - 2010
Event	International Conference on Intelligent Systems - London, United Kingdom Duration: 1 Jan 2010 → …

Conference

Conference	International Conference on Intelligent Systems
Country/Territory	United Kingdom
Period	1/01/10 → …

Cite this

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title = "Advanced modelling of complex processes by rule-based networks",

abstract = "This work presents an application of the novel theory of rule based networks for building models of processes characterised by uncertainty, non-linearity, modular structure and internal interactions. The application of the theory is demonstrated for a flotation process in the context of converting a multiple rule based system into an equivalent single rule based system by linguistic composition of the individual rule bases. During the conversion process, the transparency of the multiple rule based system is fully preserved while its accuracy is improved to a level comparable with the accuracy of the single rule based system.",

author = "Alexander Gegov and Nedyalko Petrov and B. Vatchova",

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T1 - Advanced modelling of complex processes by rule-based networks

AU - Gegov, Alexander

AU - Petrov, Nedyalko

AU - Vatchova, B.

N1 - Additional Information: DOI: 10.1109/IS.2010.5548336.

PY - 2010

Y1 - 2010

N2 - This work presents an application of the novel theory of rule based networks for building models of processes characterised by uncertainty, non-linearity, modular structure and internal interactions. The application of the theory is demonstrated for a flotation process in the context of converting a multiple rule based system into an equivalent single rule based system by linguistic composition of the individual rule bases. During the conversion process, the transparency of the multiple rule based system is fully preserved while its accuracy is improved to a level comparable with the accuracy of the single rule based system.

AB - This work presents an application of the novel theory of rule based networks for building models of processes characterised by uncertainty, non-linearity, modular structure and internal interactions. The application of the theory is demonstrated for a flotation process in the context of converting a multiple rule based system into an equivalent single rule based system by linguistic composition of the individual rule bases. During the conversion process, the transparency of the multiple rule based system is fully preserved while its accuracy is improved to a level comparable with the accuracy of the single rule based system.

M3 - Chapter (peer-reviewed)

SN - 9781424451630

SP - 197

EP - 202

BT - Intelligent Systems (IS), 2010 5th IEEE International Conference

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - International Conference on Intelligent Systems

Y2 - 1 January 2010

ER -

Advanced modelling of complex processes by rule-based networks

Abstract

Conference

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