Bio-Inspired Modeling & Learning Systems
Introduction - Research and Teaching
We are concerned with design and development of adaptive systems for industrial and business applications, based on our expertise on machine learning, (recurrent) neural networks and bio-inspired algorithms as well as different simulation methods. A central speciality of our group is the development and research on complex (i.e. multi-methodical) forecasting systems. The polysemy of the term «LEARNING SYSTEMS» is an inherent element of the group’s spirit. Our self-concept as a team is the concept of a learning system. We are keen to learn more about new methods and more about ourselves in research and teaching. We are involved in teaching at Bachelor’s and Master’s level as well as continuing education and we actively work on the development of novel teaching methods to learn for our students and together with our students.
Research Topics & Expertise
"Intelligence is based on learning"
Expertise
- Bio-inspired algorithms and neural networks
- Human in the loop machine learning
- Modeling of complex systems
- Self-learning systems for real world applications
- Forecasting methodologies
Topics
Our Team
Prof. Dr. Thomas Ott, Deputy Head of the Institute of Applied Simulation
Reference Projects
Some Projects in a Nutshell
Current publications
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Uwate, Yoko; Takamaru, Yuji; Ott, Thomas; Nishio, Yoshifumi,
2019.
Clustering using chaotic circuit networks with weighted couplings.
International journal of bifurcation and chaos.
29(4),
S. 1950053.
Verfügbar unter: https://doi.org/10.1142/S0218127419500536
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Ott, Thomas; Glüge, Stefan; Bödi, Richard; Kauf, Peter,
2019.
Economic measures of forecast accuracy for demand planning : a case-based discussion
.
In:
Braschler, M.; Stadelmann, T.; Stockinger, K., Hrsg.,
Applied Data Science.
Cham:
Springer.
S. 371-386.
Verfügbar unter: https://doi.org/10.1007/978-3-030-11821-1_20
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Glüge, Stefan; Böck, Ronald; Palm, Günther; Wendemuth, Andreas,
2014.
Neurocomputing.
141,
S. 54-64.
Verfügbar unter: https://doi.org/10.1016/j.neucom.2013.11.043
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Böck, Ronald; Glüge, Stefan; Siegert, Ingo; Wendemuth, Andreas,
2013.
Annotation and classification of changes of involvement in group conversation [Paper].
In:
Proceedings : 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction - ACII 2013.
ACII 2013 Humaine Association Conference, Geneva, 2 - 5 September 2013.
IEEE Institute of Electrical and Electronics Engineers.
S. 803-808.
Verfügbar unter: https://doi.org/10.1109/ACII.2013.150
Current projects
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An integrated modelling and learning framework for real-time online decision assistance in Swiss agriculture
Wir entwicklen einen Entscheidungsassistent der Risiken in der Landwirtschaft dank eines einzigartigen Modells, das auf der Kopplung von zuverlässigen Wetter- und saisonalen Klimavorhersagen, Bodendaten und Wachstumsprognosen basiert, beurteilen und visualisieren kann. Basierend auf Echtzeit- und historischen Wetter-, Klima-, Boden- und Kulturdaten ...
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Smartstones - KI für die Pflanzenzüchtung
Ziel des Projekts ist eine Studie zur Klärung des Potentials unterschiedlicher KI-Techniken für Optimierungen in der Pflanzenzucht auf Basis von morphologischen Eigenschaften.