SDU Education Information System
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Course Information
Course Unit Title : Optimization with MATLAB
Course Unit Code :
Type of Course Unit : Optional
Level of Course Unit : Second Cycle
Year of Study : Preb
Semester : 255.Semester
Number of ECTS Credits Allocated : 6,00
Name of Lecturer(s) : ---
Course Assistants : ---
Learning Outcomes of The Course Unit : -
Mode of Delivery : Face-To-Face
Prerequisities and Co-requisities Courses : Unavailable
Recommended Optional Programme Components : Unavailable
Course Contents : - Modeling and Developing with MATLAB
- Using optimization and AI methods
- Meta-Heuristics ve Mat-Heuristics algorithms
Languages of Instruction : Turkish
Course Goals : - Modeling and developing with MATLAB
- Using optimization and artificial intelligence methods
Course Aims : - Modeling and developing a software with MATLAB
- Solving the optimization problems
WorkPlacement   SDU MSc. in Industrial Engineering
Recommended or Required Reading
Textbook : - Lecture Notes
- MATLAB Programming Fundamentals, Mathworks, 2016.
- MATLAB Yapay Zeka ve Mühendislik Uygulamaları, Kubat C., Abaküs Yayınları, 2016.
- MATLAB: A practical approach, Attaway S., Elsevier, 2009.
- Essential MATLAB® for Engineers and Scientists, Hahn, B.D, Valentine, D. T., Elsevier, 2007.
Additional Resources : -
Material Sharing
Documents : -
Assignments : -
Exams : -
Additional Material : -
Planned Learning Activities and Teaching Methods
Lectures, Practical Courses, Presentation, Seminar, Project, Laboratory Applications (if necessary)
ECTS / Table Of Workload (Number of ECTS credits allocated)
Student workload surveys utilized to determine ECTS credits.
Activity :
Number Duration Total  
Course Duration (Excluding Exam Week) :
14 3 42  
Time Of Studying Out Of Class :
14 3 42  
Homeworks :
5 6 30  
Presentation :
0 0 0  
Project :
1 10 10  
Lab Study :
0 0 0  
Field Study :
0 0 0  
Visas :
0 0 0  
Finals :
0 0 0  
Workload Hour (30) :
30  
Total Work Charge / Hour :
0  
Course's ECTS Credit :
0      
Assessment Methods and Criteria
Studies During Halfterm :
Number Co-Effient
Visa :
1 50
Quiz :
0 0
Homework :
5 20
Attendance :
0 0
Application :
0 0
Lab :
0 0
Project :
1 30
Workshop :
0 0
Seminary :
0 0
Field study :
0 0
   
TOTAL :
100
The ratio of the term to success :
50
The ratio of final to success :
50
TOTAL :
100
Weekly Detailed Course Content
Week Topics  
1 Introduction to MATLAB Programming Language
 
2 MATLAB Functions and User-Defined Functions
 
3 Matrices, Arrays, If-Switch-Case and Loops
 
4 Solving the Linear Equations
 
5 Solving the Non-Linear Equations
 
6 Numerical Optimzation
 
7 Curve Fitting and Interpolations
 
8 Computations of the Derivates and Integrations
 
9 Symbolic Operations
 
10 Introduction to Optimization Problems
 
11 Fuzzy Logic on MATLAB
 
12 Neural Networks on MATLAB
 
13 Genetic Algorithms on MATLAB
 
14 Design a GUI
 
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