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Vague Neural Network Controller and Its Applications

Authors: Yibiao Zhao; Rui Fang; Shun Zhang; Siwei Luo;

Vague Neural Network Controller and Its Applications

Abstract

Fuzzy neural network is a promising intelligence system that combines the artificial neural network and fuzzy logic. However fuzzy neural network has its shortages: fuzzy membership function has only one single value, it cannot get more reasonable classified and cognizable results. While, vague sets theory is a generalization of fuzzy sets theory, its’ distinguishing feature is having a truth-membership function and a false-membership function. It presents both of the opposite factors to deal with nonlinearities and uncertain of control system in the control fields., this paper has been accomplished the controller of vague neural networks based on the vague set theory, this controller combines the advantage of vague set in handling uncertain information and the capability of artificial neural networks in learning process. Moreover, in the application of inverted pendulum, the character of vague neural network controller was expressed.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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