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Course Information
Course Unit Title : Intelligence Forecasting Methods
Course Unit Code : 01END5134
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 : The importance of forecasting and its models
Error/Failure analysis in forecasting models to select the best forecasting method
Intelligent models to understand the impact over the forecasting process
Mode of Delivery : Face-To-Face
Prerequisities and Co-requisities Courses : Unavailable
Recommended Optional Programme Components : Unavailable
Course Contents : Introduction to Forecasting, causal models, time series, forecasting errors, intelligence forecasting methods and computational applications
Languages of Instruction : Turkish
Course Goals : Development of the forecasting models
Error Analysis
Causal Models
Time Series Models
Intelligence Methods (ANN; FL; GST; Heuristics)
Computer Aided Applications
Course Aims : Development of the linear and non-linear forecasting models using intelligent methods
WorkPlacement   IE Computer Lab.
Recommended or Required Reading
Textbook : Lecture Notes
Additional Resources : * Research Articles
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 :
0 0 0  
Homeworks :
0 0 0  
Presentation :
0 0 0  
Project :
0 0 0  
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 :
2 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 :
50
The ratio of final to success :
50
TOTAL :
100
Weekly Detailed Course Content
Week Topics  
1 Introduction to Forecasting
 
2 Statistical Preliminaries
 
3 Causal Models I
 
4 Causal Models II
 
5 Time Series Models I
 
6 Time Series Models II
 
7 Time Series Models II
 
8 Forecasting Errors
 
9 Intelligence Forecasting Methods: Artificial Neural Networks I
 
10 Intelligence Forecasting Methods: Artificial Neural Networks II
 
11 Intelligence Forecasting Methods: Fuzzy Logic
 
12 Intelligence Forecasting Methods: Grey Systems Theory
 
13 Intelligence Forecasting Methods: Heuristics I
 
14 Intelligence Forecasting Methods: Heuristics I
 
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