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Category: Other Engineering  Computational and Machine Learning Tools for Archaeological Site Modeling (Springer Theses) free ebook download

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Author(s): Maria Elena Castiello Date: 2024 Format: pdf Language: English ISBN/ASIN: 3030885666   Pages: 314 OCR: Quality: ISBN13:   Uploader: stirkout Upload Date: 10/16/2023 1:35:28 AM       To download click on link in the Links Table below                                                                        Description: Click to see full 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. Read more Links Table     Title Link Password Size (MB) Thank to Inform Admin 3206439 Book https://nitroflare.com/view/BFEEA66901DC...   0.00 stirkout Tags: Archaeological Computational Learning Machine Modeling Site Springer Theses Tools Title Link Password Size Reason Dead link New format   Those who downloaded this book also downloaded the following books: Comments New comment:

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