Learning-based symbolic abstractions for nonlinear control systems
Symbolic models or abstractions are known to be powerful tools for the control design of
cyber–physical systems (CPSs) with logic specifications. In this paper, we investigate a …
cyber–physical systems (CPSs) with logic specifications. In this paper, we investigate a …
Prediction of Energy Consumption in Horizontal Roughing Process of Hot Rolling Strip Based on TDADE Algorithm
The steel industry is the key industry of energy consumption. The optimization of rolling
process parameters is an effective measure to reduce and optimize energy consumption …
process parameters is an effective measure to reduce and optimize energy consumption …
Timing aspects in causality analysis with multilevel flow modelling
D Kirchhübel, D Lefebvre, M Lind, S Lmansouri… - IFAC-PapersOnLine, 2022 - Elsevier
Temporal aspects of multilevel flow modelling (MFM) are important for reasoning about
causes and consequences. In particular real time reasoning about sensor data are …
causes and consequences. In particular real time reasoning about sensor data are …
Software Optimization and Orchestration for Heterogeneous and Distributed Architectures
F Lumpp - 2024 - iris.univr.it
In the context of the Edge-Cloud computing continuum, containerization and orchestration
have become two key requirements in software development best practices …
have become two key requirements in software development best practices …
Requirement Mining from Closed-Loop Control Models via Human-Computer Collaboration
P Lu, G Chen - 2024 4th International Conference on Computer …, 2024 - ieeexplore.ieee.org
This study introduces an innovative human-computer collaboration framework for mining
requirements from closed-loop control models in industrial systems. Traditional approaches …
requirements from closed-loop control models in industrial systems. Traditional approaches …