Téléchargez le livre : Computational and Machine Learning Tools for Archaeological Site Modeling

Computational and Machine Learning Tools for Archaeological Site Modeling

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Éditeur :

Springer


Collection :

Springer Theses

Paru le : 2022-01-24

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Description

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.
 
Pages
296 pages
Collection
Springer Theses
Parution
2022-01-24
Marque
Springer
EAN papier
9783030885663
EAN PDF
9783030885670
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
29
Taille du fichier
11295 Ko
Prix
232,14 €
EAN EPUB
9783030885670
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
29
Taille du fichier
106875 Ko
Prix
232,14 €

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