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An introduction to learning algorithms and potential applications in geomorphometry and Earth surface dynamics

Valentine, Andrew; Kalnins, Lara M.

Description

"Learning algorithms" are a class of computational tool designed to infer information from a data set, and then apply that information predictively. They are particularly well suited to complex pattern recognition, or to situations where a mathematical relationship needs to be modelled but where the underlying processes are not well understood, are too expensive to compute, or where signals are over-printed by other effects. If a representative set of examples of the relationship can be...[Show more]

dc.contributor.authorValentine, Andrew
dc.contributor.authorKalnins, Lara M.
dc.date.accessioned2018-11-29T22:57:16Z
dc.date.available2018-11-29T22:57:16Z
dc.identifier.issn2196-6311
dc.identifier.urihttp://hdl.handle.net/1885/153805
dc.description.abstract"Learning algorithms" are a class of computational tool designed to infer information from a data set, and then apply that information predictively. They are particularly well suited to complex pattern recognition, or to situations where a mathematical relationship needs to be modelled but where the underlying processes are not well understood, are too expensive to compute, or where signals are over-printed by other effects. If a representative set of examples of the relationship can be constructed, a learning algorithm can assimilate its behaviour, and may then serve as an efficient, approximate computational implementation thereof. A wide range of applications in geomorphometry and Earth surface dynamics may be envisaged, ranging from classification of landforms through to prediction of erosion characteristics given input forces. Here, we provide a practical overview of the various approaches that lie within this general framework, review existing uses in geomorphology and related applications, and discuss some of the factors that determine whether a learning algorithm approach is suited to any given problem.
dc.format.mimetypeapplication/pdf
dc.publisherCopernicus GmbH
dc.sourceEarth Surface Dynamics
dc.titleAn introduction to learning algorithms and potential applications in geomorphometry and Earth surface dynamics
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume4
dc.date.issued2016
local.identifier.absfor040601 - Geomorphology and Regolith and Landscape Evolution
local.identifier.ariespublicationa383154xPUB6781
local.type.statusPublished Version
local.contributor.affiliationValentine, Andrew, College of Science, ANU
local.contributor.affiliationKalnins, Lara M., University of Durham
local.bibliographicCitation.issue2
local.identifier.doi10.5194/esurf-4-445-2016
local.identifier.absseo970104 - Expanding Knowledge in the Earth Sciences
dc.date.updated2018-11-29T08:16:51Z
local.identifier.scopusID2-s2.0-84973375972
local.identifier.thomsonID000378205800009
dcterms.accessRightsOpen Access
CollectionsANU Research Publications

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