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A Supervised-Reinforced Successive Training Framework for a Fuzzy Inference System and Its Applicati...

A Supervised-Reinforced Successive Training Framework for a Fuzzy Inference System and Its Applicati...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2671795842

A Supervised-Reinforced Successive Training Framework for a Fuzzy Inference System and Its Application in Robotic Odor Source Searching

About this item

Full title

A Supervised-Reinforced Successive Training Framework for a Fuzzy Inference System and Its Application in Robotic Odor Source Searching

Publisher

Lausanne: Frontiers Research Foundation

Journal title

Frontiers in neurorobotics, 2022-05, Vol.16, p.914706-914706

Language

English

Formats

Publication information

Publisher

Lausanne: Frontiers Research Foundation

More information

Scope and Contents

Contents

Fuzzy inference systems have been widely applied in robotic control. Previous studies proposed various methods to tune the fuzzy rules and the parameters of the membership functions (MFs). Training the systems with only supervised learning requires a large amount of input-output data, and the performance of the trained system is confined by that of...

Alternative Titles

Full title

A Supervised-Reinforced Successive Training Framework for a Fuzzy Inference System and Its Application in Robotic Odor Source Searching

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_2671795842

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2671795842

Other Identifiers

ISSN

1662-5218

E-ISSN

1662-5218

DOI

10.3389/fnbot.2022.914706

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