SDU Education Information System
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Course Information
Course Unit Title :
Course Unit Code : 01INS6111
Type of Course Unit : Optional
Level of Course Unit : Second Cycle
Year of Study : 1
Semester : 1.Semester
Number of ECTS Credits Allocated : 6,00
Name of Lecturer(s) :
Course Assistants :
Learning Outcomes of The Course Unit : 1) evaluation of databases
2) modeling
3) simulation
4) fuzzy logic method
5) artificial neural networks
Mode of Delivery : Face-To-Face
Prerequisities and Co-requisities Courses : Unavailable
Recommended Optional Programme Components : Unavailable
Course Contents : Need for and use for of models, observations and measurements, developing the model, critique of models, databases, forecasting using developed models, simulations using computer, software for modeling
Languages of Instruction : Turkish
Course Goals :
Course Aims : To get databases, and simulation and modeling of them with various methods
WorkPlacement   Not Available
Recommended or Required Reading
Textbook :
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) :
16 4 64  
Time Of Studying Out Of Class :
16 3 48  
Homeworks :
1 15 15  
Presentation :
0 0 0  
Project :
0 0 0  
Lab Study :
0 0 0  
Field Study :
0 0 0  
Visas :
1 15 15  
Finals :
1 25 25  
Workload Hour (30) :
30  
Total Work Charge / Hour :
167  
Course's ECTS Credit :
6      
Assessment Methods and Criteria
Studies During Halfterm :
Number Co-Effient
Visa :
1 50
Quiz :
0 0
Homework :
1 50
Attendance :
0 0
Application :
0 0
Lab :
0 0
Project :
0 0
Workshop :
0 0
Seminary :
0 0
Field study :
0 0
   
TOTAL :
100
The ratio of the term to success :
40
The ratio of final to success :
60
TOTAL :
100
Weekly Detailed Course Content
Week Topics  
1 Introduction
 
2 Data and databases
 
3 Classical Logic
 
4 Modeling with conventional methods
 
5 Methods of modeling
 
6 Applications
 
7 Uncertainty
 
8 Membership functions
 
9 Classical and fuzzy logic
 
10 Modeling principles with fuzzy logic
 
11 Relationship in fuzzy groups
 
12 Rules and defuzzification
 
13 Artificial neural networks
 
14 Applications