id Url Resource template Resource class Title Creator Subject Description Publisher Contributor Date Type Format Identifier Language Relation Coverage Rights Alternative Title Abstract Date Created Date Issued Date Modified Medium Is Replaced By Replaces Requires Is Part Of Has Part Is Referenced By References Spatial Coverage Temporal Coverage Access Rights Bibliographic Citation License Rights Holder Cited by Cites Editor List of editors Status Doi Identifier Isbn Issn Issue Number of pages Number of volumes Pages Short title Uri Volume Name Surname Homepage Funded by Account Member Status Tag Number Current Location Is Shown At Is Shown By Europeana Rights Europeana Type Part of Is supported by Is supplied by Latitude Longitude Lat/long Has format Operating systems In series 10326 https://chloe.cnr.it/s/BiDiAr/item/10326 Academic Article bibo:AcademicArticle Artificial Neural Networks in archaeology Deravignone, Luca | Macchi Jánica, Giancarlo 2006 eng https://creativecommons.org/licenses/by-nc-nd/4.0/deed.en CC BY-NC-ND 4.0 Artificial neural networks are adaptive models that can be used for classification and pattern recognition purposes. ANNs do not differ from standard statistical models. The main difference between ANNs and traditional statistical models is their construction and definition process. In fact ANNs are adaptive in the sense that they can learn. Landscape Archaeology is a research area where the application of ANNs can be very useful. ANNs can be used for Landscape pattern recognition and Settlement systems modeling. This paper illustrate some aspects of the development of new tools and the application of ANNs in a raster GIS environment for archaeological predictive modeling purposes. https://chloe.cnr.it/s/BiDiAr/item/2002 121–136 http://www.archcalc.cnr.it/journal/id.php?id=424 17 https://www.zotero.org/groups/5293298/bidiar/items/PX5NKTP8/item-list