5 papers
Hierarchical Bayes meets hierarchical forecasting: A flexible framework for level-focused forecasts
Arwen Nugteren, Mahdi Abolghasemi, Kerrie Mengersen +1
Decision-making in hierarchical systems requires probabilistic forecasts at all cross-sectional levels. Current hierarchical forecasting methods typically generate independent fore…
Acceleration Techniques for Learning Optimal Classification Trees with Integer Programming
Mitchell Keegan, Michael Forbes, Paul Corry +1
Decision trees are a popular machine learning model which are traditionally trained by heuristic methods. Massive improvements in computing power and optimisation techniques has le…
Local vs. Global Models for Hierarchical Forecasting
Zhao Yingjie, Mahdi Abolghasemi
Hierarchical time series forecasting plays a crucial role in decision-making in various domains while presenting significant challenges for modelling as they involve multiple level…
Humans vs Large Language Models: Judgmental Forecasting in an Era of Advanced AI
MAhdi Abolghasemi, Odkhishig Ganbold, Kristian Rotaru
This study investigates the forecasting accuracy of human experts versus Large Language Models (LLMs) in the retail sector, particularly during standard and promotional sales perio…
Digital Twins for forecasting and decision optimisation with machine learning: applications in wastewater treatment
Matthew Colwell, Mahdi Abolghasemi
Prediction and optimisation are two widely used techniques that have found many applications in solving real-world problems. While prediction is concerned with estimating the unkno…