A main characteristic of archaeology is that we have to deal not only with high complexity phenomena like culture, society, and economic aspects of the past, but also with imprecise and heterogeneous datasets. The archaeological record is generally incomplete, depending on the quality of conservation, even when accurately documented. When performing quantitative analyses it is like always working on samples. The archaeological record is extremely heterogeneous and therefore trying to understand history from material culture appears as an extremely complex matter. © 2015 by Taylor & Francis Group, LLC.

Deravignone, L., Blankholm, H.P., Pizziolo, G. (2015). Predictive Modeling and Artificial Neural Networks (ANN): From Model to Survey. In B.I. Barcelo J. (a cura di), Mathematics and Archaeology (pp. 335-351). Boca Raton : CRC Press [10.1201/b18530].

Predictive Modeling and Artificial Neural Networks (ANN): From Model to Survey

Pizziolo G.
2015-01-01

Abstract

A main characteristic of archaeology is that we have to deal not only with high complexity phenomena like culture, society, and economic aspects of the past, but also with imprecise and heterogeneous datasets. The archaeological record is generally incomplete, depending on the quality of conservation, even when accurately documented. When performing quantitative analyses it is like always working on samples. The archaeological record is extremely heterogeneous and therefore trying to understand history from material culture appears as an extremely complex matter. © 2015 by Taylor & Francis Group, LLC.
2015
9781482226812
Deravignone, L., Blankholm, H.P., Pizziolo, G. (2015). Predictive Modeling and Artificial Neural Networks (ANN): From Model to Survey. In B.I. Barcelo J. (a cura di), Mathematics and Archaeology (pp. 335-351). Boca Raton : CRC Press [10.1201/b18530].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1074648