Bio-Inspired Modeling & Learning Systems
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.
"Intelligence is based on learning"
- 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
Niederberger, Thomas; Stoop, Norbert; Christen, Markus; Ott, Thomas,
Proceedings of NDES 2012.
NDES 2012, 20th Nonlinear Dynamics of Electronic Systems Conference, Wolfenbüttel, Deutschland, 11-13 July 2012.
Available from: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6293769
Ott, Thomas; Krüsi, Bertil,
2012(3), pp. 6.
Available from: https://doi.org/10.21256/zhaw-4410
Christen, Markus; Ott, Thomas; Schwarz, Daniel,
Neue Zürcher Zeitung.
Proceedings of the 2011 International Symposium on Nonlinear Theory and its Applications (NOLTA2011).
International Symposium on Nonlinear Theory and its Applications (NOLTA2011), Kobe, Japan, 4-7 September 2011.
Available from: http://www.ieice.org/proceedings/NOLTA2011/nolta11fullvol.pdf
Mürset, Urs; Ott, Thomas,
Proceedings of NDES.
NDES 2010, 18th Nonlinear Dynamics of Electronic Systems Conference, 2010.
Classification of drone signals
Predictive Analytics for Hospital Supply Chain Management
Preliminary/feasibility study for a comprehensive AI-based solution in hospitals for demand-oriented assortment and efficient inventory Management ordering with a focus on security of supply and cost Efficiency planning of reprocessing planning of personnel deployment cost and income planning ...