Computational and machine learning tools for archeological site modeling / Maria Elena Castiello.
Castiello, Maria Elena.
2022
CC80.4
Available Online

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Title Computational and machine learning tools for archeological site modeling / Maria Elena Castiello.
Author Castiello, Maria Elena.
ISBN 9783030885670 (electronic bk.)
3030885674 (electronic bk.)
3030885666
9783030885663
DOI https://doi.org/10.1007/978-3-030-88567-0
Imprint Cham, Switzerland : Springer, 2022.
Language English
Description 1 online resource
Other Standard Identifiers 10.1007/978-3-030-88567-0 doi
Call Number CC80.4
Dewey Decimal Classification 930.10285/631
Summary 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.
Note "Doctoral Thesis accepted by University of Bern, Switzerland."
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed February 9, 2022).
Series Springer theses, 2190-5061
Available in Other Form Print version: 9783030885663
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Record Appears in Online Resources > Ebooks
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Introduction
Space, Environment and Quantitative approaches in Archaeology
Predictive Modeling
Materials and Data.

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