ARITHMĪTIKES METHODOI EPILYSĪS MERIKŌN DIAFORIKŌN EXISŌSEŌN KAI EFARMOGES

Course Information
TitleΑΡΙΘΜΗΤΙΚΕΣ ΜΕΘΟΔΟΙ ΕΠΙΛΥΣΗΣ ΜΕΡΙΚΩΝ ΔΙΑΦΟΡΙΚΩΝ ΕΞΙΣΩΣΕΩΝ ΚΑΙ ΕΦΑΡΜΟΓΕΣ / ARITHMĪTIKES METHODOI EPILYSĪS MERIKŌN DIAFORIKŌN EXISŌSEŌN KAI EFARMOGES
CodeΣΜΥ023
FacultySciences
SchoolMathematics
Cycle / Level2nd / Postgraduate
Teaching PeriodWinter/Spring
CoordinatorEfthymios Karatzas
CommonNo
StatusActive
Course ID600025959

Programme of Study: PMS Tmīmatos Mathīmatikṓn (2025-2030)

Registered students: 0
OrientationAttendance TypeSemesterYearECTS
STATISTIKĪ, MONTELOPOIĪSĪ KAI YPOLOGISTIKES METHODOIElective Courses belonging to the selected specializationWinter-10

Class Information
Academic Year2025 – 2026
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Total Hours39
Class ID
600268406
Course Type 2021
General Foundation
Mode of Delivery
  • Face to face
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction, Examination)
Prerequisites
General Prerequisites
Fundamental numerical and mathematical analysis and a programming language knowledge.
Learning Outcomes
Upon successful completion of the course, students should understand initial value problems and be able to analyze and solve differential equations as well as systems of linear differential equations. Understand the role of continuous problem stability, order of accuracy and various stability properties of numerical methods for initial value problems. Know the basic numerical methods for initial value problems, as well as their advantages and disadvantages. To be able to implement the aforementioned methods on the computer.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Work autonomously
  • Work in teams
  • Work in an interdisciplinary team
Course Content (Syllabus)
Initial-value and boundary-value problems. Numerical methods for solving ordinary differential equations with initial conditions and/or boundary conditions. Linear and non-linear Shooting methods. Linear and non-linear finite difference methods. Calculus of variations techniques. Introduction to finite element method. Finite element methods for elliptic, parabolic, and hyperbolic problems.
Keywords
Numerical Analysis, Numerical Analysis for Partial Defferential Equations.
Educational Material Types
  • Slide presentations
  • Video lectures
  • 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
Description
Slides projector, computer.
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures75
Seminars25
Laboratory Work50
Reading Assigment150
Exams0
Total300
Student Assessment
Description
Αssignment, presentation of assignment, written exams.
Student Assessment methods
  • Written Exam with Short Answer Questions (Formative)
  • Written Exam with Extended Answer Questions (Formative)
  • Written Assignment (Formative)
  • Oral Exams (Summative)
  • Performance / Staging (Summative)
  • Written Exam with Problem Solving (Formative)
  • Report (Summative)
Bibliography
Course Bibliography (Eudoxus)
-Αριθμητικές Μέθοδοι για Συνήθεις Διαφορικές Εξισώσεις, Γ. Δ. Ακρίβη και Β. Α. Δουγαλή, Πανεπιστημιακές Εκδόσεις Κρήτης, Ηράκλειο, δεύτερη έκδοση, 2013. -Αριθμητική Ανάλυση: Συνήθεις Διαφορικές Εξισώσεις, Μ. Ν. Βραχάτη, Εκδόσεις Κλειδάριθμος, Αθήνα, 2012.
Additional bibliography for study
[1] Α. Quarteroni, R. Sacco, and F. Saleri, “Numerical Mathematics”, Springer-Verlag 2007. [2] A. Ern and J. L. Guermond, Theory and Practice of Finite Elements, Springer, 2000. [3] A. Friedman, “Mathematics in Industrial Problems”, Part 8, The IMA Volumes in Mathematics and its Applications, Springer New York, 1996. [4] A. Friedman, C. Y. Kao, “Mathematical Modeling of Biological Processes”, Springer International Publishing, 2014. [5] M. Asch, “A Toolbox for Digital Twins : From Model-Based to Data-Driven” Society for Industrial and Applied Mathematics SIAM, Philadelphia, 2022. [6] J.S. Hesthaven, G. Rozza, B Stamm, “Certified Reduced Basis Methods for Parametrized Partial Differential Equations”, SpringerBriefs in Mathematics, 2016.
Last Update
15-09-2025