222.139 Soft Computing in Hydraulic and Structural Engineering Theory and Practice
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2019S, VO, 2.0h, 3.0EC


  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VO Lecture

Aim of course

Theory and practice - 30 hrs 3 ECTS credits Soft computing (SC)-artificial neural networks (ANNs), evolutionary algorithms and fuzzy inference systems is a counterpart of conventional (hard) methods of computing. The aim of the course is to present mathematical foundations of SC, to analyze various applications in hydro and structural engineering. This course describes from an engineering point of view a detailed treatment of ANNs. The most popular neural network architectures and learning algorithms for supervised and unsupervised learning are covered.

Subject of course

The course is supported with examples, numerical experiments and applications. The participants learn to implement and apply algorithms using Matlab. The course contents theory (50%) and practice (50%) equally to 30 hrs lectures and exercises.The subject matter is prepared at a level suitable for use for graduate, master and PhD students, post docs and researchers.


  • Mavrova-Guirguinova, Maria


Course dates

Tue18:00 - 18:3002.04.2019 EDV Raum, KarlsplatzVorbesprechung

Course registration

Not necessary



No lecture notes are available.