Titlebook: Computational and Machine Learning Tools for Archaeological Site Modeling; Maria Elena Castiello Book 2022 The Editor(s) (if applicable) a

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https://doi.org/10.1007/978-3-030-88567-0Machine Learning in Archaeology; Random Forest in Archaeology; Computers Application in Archaeology; Co

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978-3-030-88569-4The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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Symptome der Haut/Hautanhangsgebilde,elationships, while framing the research within the wider context of landscape archaeological studies. Here, a synopsis of the ‘Landscape archaeology’ concept is provided and an introduction to Geographic Information Systems (GIS) is given with respect to their specific use for Archaeological Site M

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,Verzeichnis der verwendeten Abkürzungen,sentation of the gathered datasets is given, providing with some insights on their first restructuring and modeling. For the first time, this study explores and analyses the archaeological records from different Swiss cantons (Zurich, Aargau, Grisons, Fribourg, Geneva, Vaud) in a comprehensive and c

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Symptomorientierte onkologische Therapiea large archaeological site data base. The present chapter gives detailed insights in the methodology developed in this Thesis and the steps followed for setting the Archaeological Site Modeling procedure. The first part is dedicated to the conceptual modeling approach used to correct data biases an

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