700.372 (21S) Optimisation and Neural Network based Simulation Lab for Transportation and Logistics
Überblick
Weitere Informationen zum Lehrbetrieb vor Ort finden Sie unter: https://www.aau.at/corona.
- Lehrende/r
- LV-Titel englisch Optimisation and Neural Network based Simulation Lab for Transportation and Logistics
- LV-Art Kurs (prüfungsimmanente LV )
- LV-Modell Onlinelehrveranstaltung
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 3.0
- Anmeldungen 6 (30 max.)
- Organisationseinheit
- Unterrichtssprache Englisch
- LV-Beginn 02.03.2021
- eLearning zum Moodle-Kurs
- Seniorstudium Liberale Ja
Zeit und Ort
LV-Beschreibung
Intendierte Lernergebnisse
This lecture familiarizes students with the fundamentals of optimization and neural networks. Selected applications are considered in various fields of engineering including transportation.
The general expectation regarding the knowledge to be provided/acquired is as follows:
- Mastering of the basics of optimization and selected applications
- Mastering of the basics of neural networks and selected applications
- Mastering of some MATLAB Toolboxes (e.g. Linear programming and Quadratic programming toolboxes) and their application in solving linear and nonlinear optimization problems.
- Mastering of Recurrent Neural Networks and their application in solving linear and nonlinear optimization problems.
- Mastering of the use of Neural networks to solve algebraic equations
- Mastering of the use of Neural networks for traffic flow counting
- Mastering of the use of Neural networks to implement logic gates
- Mastering of the development of simulation algorithms (based on Recurrent Neural Networks) for the solving of shortest path problems in graph networks.
- Mastering of the development of simulation algorithms (based on Recurrent Neural Networks) for the solving of traveling salesman problems in graph networks.
Lehrmethodik inkl. Einsatz von eLearning-Tools
The slides are available for the entire lecture. These slides are uploaded into the MOODLE system. The entire content of each slide is systematically explained by the lecturer.
Additional examples that are not included in the slides are suggested by the lecturer to allow a good understanding of the information provided.
The slides contain exercises with solutions to allow a good understanding of the contents of each chapter. These solutions are systematically explained (during the lecture) by the lecturer.
The Lecturer provides full explanation of how to write numerical codes to solve the exercises proposed in each chapter of the Lecture.
Inhalt/e
The lecture is organized around the following topics:
1. Fundamentals of optimization
2. Fundamentals of Neural Networks and Recurrent Neural Networks
3. Models of artificial neurons
4. Learning mechanism
5. Single-layer perceptron
6. Multi-layer perceptron
7. Neural Networks based linear optimization
8. Neural Networks based quadratic optimization
9. Neural Networks based solving of algebraic equations
10. Neural Networks based traffic flow counting
11. Neural Networks based implementation of logic gates (AND, NAND, OR, NOR, XOR. XNOR)
12. Neural Networks based high order nonlinear optimization
13. Neural Networks based shortest path detection
14. Neural Networks based travel salesman problem detection
15. Neural Networks based - Binary Classification
16. Radial basis function networks
17. Principal component analysis
18. Self-organizing map
Prüfungsinformationen
Beurteilungsschema
Note BenotungsschemaPosition im Curriculum
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Fach: Information and Communications Engineering: Supplements (NC, ASR)
(Wahlfach)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
- 700.372 Optimisation and Neural Network based Simulation Lab for Transportation and Logistics (2.0h KS / 3.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
-
Fach: Information and Communications Engineering: Supplements (NC, ASR)
(Wahlfach)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Fach: Technical Complements (NC, ASR)
(Wahlfach)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
- 700.372 Optimisation and Neural Network based Simulation Lab for Transportation and Logistics (2.0h KS / 3.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
-
Fach: Technical Complements (NC, ASR)
(Wahlfach)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Fach: Information and Communications Engineering: Supplements (NC, ASR)
(Wahlfach)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
- 700.372 Optimisation and Neural Network based Simulation Lab for Transportation and Logistics (2.0h KS / 3.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
-
Fach: Information and Communications Engineering: Supplements (NC, ASR)
(Wahlfach)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Fach: Technical Complements (NC, ASR)
(Wahlfach)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
- 700.372 Optimisation and Neural Network based Simulation Lab for Transportation and Logistics (2.0h KS / 3.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
-
Fach: Technical Complements (NC, ASR)
(Wahlfach)
Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung
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Sommersemester 2023
- 700.372 KS Optimisation and Neural Network based Simulation Lab for Transportation and Logistics (2.0h / 3.0ECTS)
-
Wintersemester 2022/23
- 700.372 KS Optimisation and Neural Network based Simulation Lab for Transportation and Logistics (2.0h / 3.0ECTS)
-
Sommersemester 2022
- 700.372 KS Optimisation and Neural Network based Simulation Lab for Transportation and Logistics (2.0h / 3.0ECTS)
-
Sommersemester 2020
- 700.372 KS Optimisation and Neural Network based Simulation Lab for Transportation and Logistics (2.0h / 3.0ECTS)
-
Wintersemester 2018/19
- 700.372 KS Optimisation and Neural Network based Simulation Lab for Transportation and Logistics (2.0h / 3.0ECTS)
-
Wintersemester 2017/18
- 700.372 KS Simulation Lab for Transportation and Logistics (2.0h / 3.0ECTS)
-
Wintersemester 2016/17
- 700.372 KS Simulation Lab for Transportation and Logistics (2.0h / 3.0ECTS)
-
Wintersemester 2015/16
- 700.372 KS Simulation Lab for Transportation and Logistics (2.0h / 3.0ECTS)
-
Wintersemester 2014/15
- 700.372 KU Simulation Lab for Transportation and Logistics (1.0h / 1.5ECTS)
-
Wintersemester 2013/14
- 700.372 KU Simulation Lab for Transportation and Logistics (1.0h / 1.5ECTS)
-
Wintersemester 2012/13
- 700.372 KU Simulation Lab for Transportation and Logistics (2.0h / 3.0ECTS)