222.139 Soft Computing in Hydraulic and Structural Engineering Theory and Practice
Diese Lehrveranstaltung ist in allen zugeordneten Curricula Teil der STEOP.
Diese Lehrveranstaltung ist in mindestens einem zugeordneten Curriculum Teil der STEOP.

2019S, VO, 2.0h, 3.0EC


  • Semesterwochenstunden: 2.0
  • ECTS: 3.0
  • Typ: VO Vorlesung

Ziele der Lehrveranstaltung

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.

Inhalt der Lehrveranstaltung

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


LVA Termine

Di.18:00 - 18:3002.04.2019 EDV Raum, KarlsplatzVorbesprechung


Nicht erforderlich



Es wird kein Skriptum zur Lehrveranstaltung angeboten.