Forecasting with Artificial Intelligence Theory and Applications

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 (Inform...

Full description

Bibliographic Details
Other Authors: Hamoudia, Mohsen (Editor), Makridakis, Spyros (Editor), Spiliotis, Evangelos (Editor)
Format: eBook
Language:English
Published: Cham Palgrave Macmillan 2023, 2023
Edition:1st ed. 2023
Series:Palgrave Advances in the Economics of Innovation and Technology
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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.