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Neurocomputing
Article . 2002 . Peer-reviewed
License: Elsevier TDM
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A Lagrangian augmented Hopfield network for mixed integer non-linear programming problems

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2002 English Publisher:Elsevier BVJournal:Neurocomputing, volume 42, pages 323-330 (issn: 0925-2312, Copyright policy )Publicly funded
Authors: Joseph D. Dillon; Mark J. O'Malley;

doi: 10.1016/s0925-2312(01)00585-9

A Lagrangian augmented Hopfield network for mixed integer non-linear programming problems

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Keywords

augmented Hopfield network, Learning and adaptive systems in artificial intelligence, augmented Lagrangian function

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    popularity
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    influence
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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!
12
Top 10%
Average
Average
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