Maria Elena Castiello
Computational and Machine Learning Tools for Archaeological Site Modeling
Computational and Machine Learning Tools for Archaeological Site Modeling
💎 Earn 916 Points (£9.16) on this item.
YOU SAVE £36.74
- Condition: Brand new
- UK Delivery times: Usually arrives within 2 - 3 working days
- UK Shipping: Fee starts at £2.39. Subject to product weight & dimension
Bulk ordering. Want 15 or more copies? Get a personalised quote and bigger discounts. Learn more about bulk orders.
Couldn't load pickup availability
- More about Computational and Machine Learning Tools for Archaeological Site Modeling
This book uses machine learning to address archaeological problems such as site detection and locational preferences, analyzing institutional data from six Swiss regions. It demonstrates how the Random Forest algorithm can assist in modeling processes with heterogeneous and incomplete datasets and provides an in-depth review of quantitative methods for archaeological predictive modeling. It is a valuable resource for academics and professionals in archaeology and cultural heritage management.
Format: Paperback / softback
Length: 296 pages
Publication date: 26 January 2023
Publisher: Springer Nature Switzerland AG
This captivating book delves into a groundbreaking machine-learning-based approach to address a range of traditional archaeological challenges, including archaeological site detection and site locational preferences. By utilizing institutional data collected from six Swiss regions (Zurich, Aargau, Grisons, Vaud, Geneva, and Fribourg), the author has developed an innovative conceptual framework rooted in the powerful Random Forest algorithm. Through meticulous analysis, the book showcases how this algorithm can effectively aid in modeling processes, particularly when dealing with diverse and incomplete archaeological datasets and associated cultural heritage information. Moreover, an extensive review of past and recent quantitative methods for archaeological predictive modeling is presented, providing valuable insights for readers.
The book serves as a comprehensive guide, equipping readers with the necessary tools to establish their protocol for handling uncertain data, predicting archaeological site locations, assessing the importance of environmental features, and proposing a robust model validation procedure. Its interdisciplinary appeal extends to academics and professionals in archaeology and cultural heritage management, offering a rich source of inspiration for future research endeavors in the realm of digital humanities and computational archaeology.
Weight: 486g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030885694
Edition number: 1st ed. 2022
This item can be found in:
UK and International shipping information
UK and International shipping information
UK Delivery and returns information:
- Delivery within 2 - 3 days when ordering in the UK.
- Shipping fee for UK customers from £2.39. Fully tracked shipping service available.
- Returns policy: Return within 30 days of receipt for full refund.
International deliveries:
Shulph Ink now ships to Australia, Belgium, Canada, France, Germany, Ireland, Italy, India, Luxembourg Saudi Arabia, Singapore, Spain, Netherlands, New Zealand, United Arab Emirates, United States of America.
- Delivery times: within 5 - 10 days for international orders.
- Shipping fee: charges vary for overseas orders. Only tracked services are available for most international orders. Some countries have untracked shipping options.
- Customs charges: If ordering to addresses outside the United Kingdom, you may or may not incur additional customs and duties fees during local delivery.
