Overview
- Delineates what the capabilities of modern forecasting approaches
- Offers comprehensive case studies on various critical domains and describes best practices
- Covers a range of cutting-edge topics, including data mining techniques and predictive algorithms
Part of the book series: Palgrave Advances in the Economics of Innovation and Technology (PAEIT)
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Table of contents (14 chapters)
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Front Matter
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Artificial Intelligence: Present and Future
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Front Matter
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The Status of Machine Learning Methods for Time Series and New Product Forecasting
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Front Matter
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Global Forecasting Models
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Front Matter
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Meta-Learning and Feature-Based Forecasting
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Front Matter
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Special Applications
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Front Matter
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Keywords
About this book
This book is a comprehensive guide that explores the intersection of artificial intelligence and forecasting, providing the latest insights and trends in this rapidly evolving field.
The book contains fourteen chapters covering a wide range of topics, including the concept of AI, its impact on economic decision-making, traditional and machine learning-based forecasting methods, challenges in demand forecasting, global forecasting models, meta-learning and feature-based forecasting, ensembling, deep learning, scalability in industrial and optimization applications, and forecasting performance evaluation. With key illustrations, state-of-the-art implementations, best practices, and notable advances, this book offers practical insights into the theory and practice of AI-based forecasting. This book is a valuable resource for anyone involved in forecasting, including forecasters, statisticians, data scientists, business analysts, or decision-makers.
Editors and Affiliations
About the editors
Mohsen Hamoudia is CEO since 2020 of PREDICONSULT (Data and Predictive Analytics), Paris. He is a consultant to several consulting companies in Europe and the US. His research is primarily focused on economics and empirical aspects of forecasting in air transportation, telecommunications, IT (Information and Technologies), social networking, and innovation and new technologies
Spyros Makridakis is a Professor at the University of Nicosia and the founder of the Makridakis Open Forecasting Center (MOFC). He is also an Emeritus Professor at INSEAD, he joined in 1970. He has authored/co-authored, 27 books/special and more than 360 articles. He was the founding editor-in-chief of the Journal of Forecasting and the International Journal of Forecasting and is the organizer of the renowned M (Makridakis) competitions.Evangelos Spiliotis is a Research Fellow at the Forecasting & Strategy Unit, National Technical University of Athens. Hisresearch focuses on time series forecasting with machine learning, while his work on tools for management support. He has co-organized the M4, M5, and M6 forecasting competitions.
Bibliographic Information
Book Title: Forecasting with Artificial Intelligence
Book Subtitle: Theory and Applications
Editors: Mohsen Hamoudia, Spyros Makridakis, Evangelos Spiliotis
Series Title: Palgrave Advances in the Economics of Innovation and Technology
DOI: https://doi.org/10.1007/978-3-031-35879-1
Publisher: Palgrave Macmillan Cham
eBook Packages: Economics and Finance, Economics and Finance (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-35878-4Published: 21 September 2023
Softcover ISBN: 978-3-031-35881-4Due: 22 October 2023
eBook ISBN: 978-3-031-35879-1Published: 20 September 2023
Series ISSN: 2662-3862
Series E-ISSN: 2662-3870
Edition Number: 1
Number of Pages: XLIV, 412
Number of Illustrations: 10 b/w illustrations, 38 illustrations in colour
Topics: Economics, general, Artificial Intelligence, Theory of Computation