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improve: meaningfulness – i.e. specify two hatnote templates for redirecting to 'spatial networks' or avoiding confusions about the polysemic term/abbreviation: 'SNN' Tag: Disambiguation links added |
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{{Short description|Category of tailored neural networks}}
{{distinguish|Spatial network}}{{other uses|SNN (disambiguation)}}
<onlyinclude>'''Spatial neural networks''' ('''SNNs''') or '''geographically weighted neural networks''' ('''GWNNs'''), constitute a supercategory of tailored [[artificial neural networks|neural networks (NNs)]] for representing and predicting geographic phenomena. They generally improve both the statistical [[Accuracy and precision|accuracy]] and [[Statistical reliability|reliability]] of the a-spatial/classic NNs whenever they handle [[Geographic data and information|geo-spatial datasets]], and also of the other spatial [[Statistical model|(statistical) models]] (e.g. spatial regression models) whenever the geo-spatial [[data set|datasets]]' variables depict [[Nonlinear system|non-linear relations]].<ref name="Morer et al. (2020)"/><ref name="Gupta et al. (2021)"/><ref name="Hagenauer et al. (2021)"/></onlyinclude>
<includeonly>Examples of SNNs are OSFA spatial neural networks, SVANNs and GWNNs.</includeonly>
==History==
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