ENBIS-23 Valencia Conference

Session

CONTRIBUTED Machine Learning 2

12 Sept 2023, 08:30

2.9/2.10

Conveners

CONTRIBUTED Machine Learning 2

• Jean-Michel Poggi (University of Paris-Saclay)

172. Practical Reinforcement Learning in Logistics

Jan-Willem Bikker (CQM)

12/09/2023, 08:30

Machine learning

Reinforcement learning is a variant on optimization, formulated as a Markov Decision Problem, and is seen as a branch of machine learning. CQM, a consultancy company, has decades of experience in Operations Research in logistics and supply chain projects. CQM performed a study in which reinforcement learning was applied to a logistics case on tank containers. Because of inbalanced flows, these...

105. Near Real-Time Prediction of Hospital Performance Metrics Using Scalable Random Forest Algorithm

Richard Wood (National Health Service)

12/09/2023, 08:50

Machine learning

While previous studies have shown the potential value of predictive modelling for emergency care, few models have been practically implemented for producing near real-time predictions across various demand, utilisation and performance metrics. In this study, 33 independent Random Forest (RF) algorithms were developed to forecast 11 urgent care metrics over a 24-hour period across three...

106. Local Linear Forests as a Solution for Online Process Control

Mrs Lucile Terras (EMSE (Ecole des Mines de Saint-Etienne))

12/09/2023, 09:10

Machine learning

In this study, we propose to use the Local Linear Forest (R. Friedberg et al., 2020) to forecast the best equipment condition from complex and high-dimensional semiconductor production data. In a static context, the analysis performed on real production data shows that Local Linear Forests outperform the traditional Random Forest model and 3 other benchmarks. Each model is finally integrated...