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Computational and Machine Learning Tools for Archaeological Site Modeling

Language EnglishEnglish
Book Hardback
Book Computational and Machine Learning Tools for Archaeological Site Modeling Maria Elena Castiello
Libristo code: 38503919
Publishers Springer Nature Switzerland AG, January 2022
This book describes a novel machine-learning based approach to answer some traditional archaeologi... Full description
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247.35 €
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This book describes a novel machine-learning based approach to answer some traditional archaeological problems, relating to archaeological site detection and site locational preferences. Institutional data collected from six Swiss regions (Zurich, Aargau, Grisons, Vaud, Geneva and Fribourg) have been analyzed with an original conceptual framework based on the Random Forest algorithm. It is shown how the algorithm can assist in the modelling process in connection with heterogeneous, incomplete archaeological datasets and related cultural heritage information. Moreover, an in-depth review of past and more recent works of quantitative methods for archaeological predictive modelling is provided. The book guides the readers to set up their own protocol for: i) dealing with uncertain data, ii) predicting archaeological site location, iii) establishing environmental features importance, iv) and suggest a model validation procedure. It addresses both academics and professionals in archaeology and cultural heritage management, and offers a source of inspiration for future research directions in the field of digital humanities and computational archaeology.

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About the book

Full name Computational and Machine Learning Tools for Archaeological Site Modeling
Language English
Binding Book - Hardback
Date of issue 2022
Number of pages 296
EAN 9783030885663
Libristo code 38503919
Weight 641
Dimensions 155 x 235 x 23
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