196 citations · 723 across the 27 of their papers we have counts for
3 papers · 2 filters
Optimization with Trained Machine Learning Models Embedded
Artur M. Schweidtmann, Dominik Bongartz, Alexander Mitsos
Trained ML models are commonly embedded in optimization problems. In many cases, this leads to large-scale NLPs that are difficult to solve to global optimality. While ML models fr…
Normalizing Flow-based Day-Ahead Wind Power Scenario Generation for Profitable and Reliable Delivery Commitments by Wind Farm Operators
Eike Cramer, Leonard Paeleke, Alexander Mitsos +1
We present a specialized scenario generation method that utilizes forecast information to generate scenarios for day-ahead scheduling problems. In particular, we use normalizing fl…
Identification of MIMO Wiener-type Koopman Models for Data-Driven Model Reduction using Deep Learning
Jan C. Schulze, Danimir T. Doncevic, Alexander Mitsos
We use Koopman theory to develop a data-driven nonlinear model reduction and identification strategy for multiple-input multiple-output (MIMO) input-affine dynamical systems. While…