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Computational and machine learning t...
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Castiello, Maria Elena.
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Computational and machine learning tools for archaeological site modeling
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Computational and machine learning tools for archaeological site modeling/ by Maria Elena Castiello.
作者:
Castiello, Maria Elena.
出版者:
Cham :Springer International Publishing : : 2022.,
面頁冊數:
xviii, 296 p. :ill., digital ;24 cm.
附註:
"Doctoral Thesis accepted by University of Bern, Switzerland."
內容註:
Introduction -- Space, Environment and Quantitative approaches in Archaeology -- Predictive Modeling -- Materials and Data.
Contained By:
Springer Nature eBook
標題:
Archaeology - Data processing. -
電子資源:
https://doi.org/10.1007/978-3-030-88567-0
ISBN:
9783030885670
Computational and machine learning tools for archaeological site modeling
Castiello, Maria Elena.
Computational and machine learning tools for archaeological site modeling
[electronic resource] /by Maria Elena Castiello. - Cham :Springer International Publishing :2022. - xviii, 296 p. :ill., digital ;24 cm. - Springer theses,2190-5061. - Springer theses..
"Doctoral Thesis accepted by University of Bern, Switzerland."
Introduction -- Space, Environment and Quantitative approaches in Archaeology -- Predictive Modeling -- Materials and Data.
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.
ISBN: 9783030885670
Standard No.: 10.1007/978-3-030-88567-0doiSubjects--Topical Terms:
948938
Archaeology
--Data processing.
LC Class. No.: CC80.4 / .C37 2022
Dewey Class. No.: 930.10285631
Computational and machine learning tools for archaeological site modeling
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