SPECIAL TOPICS AND APPLICATIONS OF DATA ADJUSTMENT
| Title | ΕΙΔΙΚΑ ΘΕΜΑΤΑ ΣΥΝΟΡΘΩΣΕΩΝ ΚΑΙ ΕΦΑΡΜΟΓΕΣ / SPECIAL TOPICS AND APPLICATIONS OF DATA ADJUSTMENT |
| Code | Α35 |
| Faculty | Engineering |
| School | Rural and Surveying Engineering |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Spring |
| Coordinator | Christoforos Kotsakis |
| Common | No |
| Status | Active |
| Course ID | 20000892 |
Programme of Study: PPS Tmīmatos Agronómōn kai Topográfōn Mīchanikṓn (2025-sīmera)
Registered students: 0
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|
Programme of Study: UPS of School of Rural and Surveing Engineering
Registered students: 54
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| Geodesy and Surveying | Compulsory Courses | 8 | 4 | 6 |
| Cadastre, Photogrammetry and Cartography | Elective Courses | 8 | 4 | 6 |
| Transportation and Hydraulic Engineering | Elective Courses | 8 | 4 | 6 |
| Academic Year | 2019 – 2020 |
| Class Period | Spring |
| Faculty Instructors | |
| Weekly Hours | 4 |
| Class ID | 600153331
|
Class Schedule
| Building | Πολυτεχνείο - πτέρυγα Γ (ΤΗΜΜΥ & Τοπογράφων Μηχ.) |
| Floor | Όροφος 2 |
| Hall | 307 (13) |
| Calendar | Πέμπτη 12:00 έως 15:00 |
Course Type 2016-2020
- Background
- General Knowledge
- Scientific Area
- Skills Development
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600153331
- Other: http://users.auth.gr/kotsaki/
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Linear algebra and matrices, Basic principles from statistics theory, Least-squares adjustment theory, Fundamentals of Surveying and Geodesy, Coordinate systems and reference frames.
Learning Outcomes
After the successful completion of this course, the students will be able to apply basic knowledge from least squares theory to resolve special types of data adjustment problems, such as:
(1) interpolation and predicition of unknown signals from discrete observations based on stochastic models,
(2) optimal parameter estimation in ill-conditioned linear models, and
(3) data adjustment problems with dynamic models based on Kalman filtering.
The students will learn essential techniques for the numerical solution of the above problems based on the use of Matlab programming language.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Adapt to new situations
- Make decisions
- Work autonomously
- Work in teams
- Work in an international context
- Work in an interdisciplinary team
- Generate new research ideas
- Advance free, creative and causative thinking
Course Content (Syllabus)
1) Review of basic principles from least-squares theory
2) Adjustment problems with extended models
3) Adjustment problems with weak or ill-conditioned models and regularized parameter estimation techniques
4) Adjustment problems with dynamical models via Kalman filtering techniques
5) Adjustment problems for determining "multivariate mean values" and optimal fitting of multiple spatial datasets
6) Adjustment problems for estimating unknown functions via stochastic modeling
7) Examples - Applications
Keywords
Data analysis, parameter estimation, adjustment theory, inverse problems in surveying engineering applications
Educational Material Types
- Notes
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
- Use of ICT in Communication with Students
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 15 | ✓ | |||
| Seminars | 15 | ✓ | |||
| Tutorial | 10 | ✓ | |||
| Total | 40 |
Student Assessment
Student Assessment methods
- Written Assignment (Formative, Summative)
- Oral Exams (Formative, Summative)
- Written Exam with Problem Solving (Formative, Summative)
- Report (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
1) Δερμάνης Α. (1987) Συνόρθωση παρατηρήσεων και θεωρία εκτίμησης (τόμος Β), Εκδ. Ζήτη.
2) Α. Δερμάνης, Α. Φωτίου (1997) Μέθοδοι και εφαρμογές συνόρθωσης παρατηρήσεων, Εκδ. Ζήτη.
Additional bibliography for study
1) Strang G., Borre K. (1997) Linear algebra, Geodesy and GPS. Wellesley-Cambridge Press, Wellesley, MA.
2) Ghilani C.D. (2010) Adjustment computations & spatial data analysis. John Wiley & Sons, Inc., Hoboken, New Jersey.
3) Teunissen P.J.G. (2000) Adjustment theory: an introduction. Series on Mathematical Geodesy and Positioning, Delft University Press.
4) Teunissen P.J.G. (2000) Testing theory: an introduction. Series on Mathematical Geodesy and Positioning, Delft University Press.
Last Update
03-06-2020
