Forecasting with Artificial Intelligence: Theory and Applications

Author:   Mohsen Hamoudia ,  Spyros Makridakis ,  Evangelos Spiliotis
Publisher:   Springer International Publishing AG
Edition:   2023 ed.
ISBN:  

9783031358784


Pages:   412
Publication Date:   21 September 2023
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Forecasting with Artificial Intelligence: Theory and Applications


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Author:   Mohsen Hamoudia ,  Spyros Makridakis ,  Evangelos Spiliotis
Publisher:   Springer International Publishing AG
Imprint:   Palgrave Macmillan
Edition:   2023 ed.
Weight:   0.719kg
ISBN:  

9783031358784


ISBN 10:   3031358783
Pages:   412
Publication Date:   21 September 2023
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Part I. Artificial intelligence : present and future.- 1. Human intelligence (HI) versus artificial intelligence (AI) and intelligence augmentation (IA).- 2. Expecting the future: How AI's potential performance will shape current behavior.- Part II. The status of machine learning methods for time series and new products forecasting.- 3. Forecasting with statistical, machine learning, and deep learning models: Past, present and future.- 4. Machine Learning for New Product Forecasting.- Part III. Global forecasting models.- 5. Forecasting in Big Data with Global Forecasting Models.- 6. How to leverage data for Time Series Forecasting with Artificial Intelligence models: Illustrations and Guidelines for Cross-learning.- 7. Handling Concept Drift in Global Time Series Forecasting.- 8. Neural network ensembles for univariate time series forecasting.- Part IV. Meta-learning and feature-based forecasting.- 9. Large scale time series forecasting with meta-learning.- 10. Forecasting large collections of time series: feature-based methods.- Part V. Special applications.- 11. Deep Learning based Forecasting: a case study from the online fashion industry.- 12. The intersection of machine learning with forecasting and optimisation: theory and applications.- 13. Enhanced forecasting with LSTVAR-ANN hybrid model: application in monetary policy and inflation forecasting.- 14. The FVA framework for evaluating forecasting performance. 

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Author Information

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.

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