Course Name Code Semester T+U Hours Credit ECTS
Soft Computing Methods and Applications ENM 555 0 3 + 0 3 6
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level yuksek_lisans
Course Type Optional
Course Coordinator Dr.Öğr.Üyesi ALPER KİRAZ
Course Lecturers
Course Assistants
Course Category Field Proper Education
Course Objective


Using soft computing methods for modeling problems including multivariable and multi-parameter and difficult to model, solving these kind of problems with soft computing methods and interpreting results.

Course Content

Principal concepts of soft computing, Fuzzy set theory and applications, Principal concepts of Neuro-computing and applications pf artificial neural networks, Evolutionary computing and applications of Genetic Algorithms, Importance of soft computing in fuzzy decision making, applications of soft computing methods on Matlab toolboxes and interpreting results.

# Course Learning Outcomes Teaching Methods Assessment Methods
1 Students know the principal concepts of soft computing , , , , , ,
2 Students are informed of methods of soft computing , , , , , , ,
3 Students define and solve problems using soft computing methods , , , , , , , , ,
4 Students are informed of decision making techniques , , , , , ,
5 Students Define and solve problems using decision making techniques , , , , , , , , ,
Week Course Topics Preliminary Preparation
1 Basic concepts of Soft Computing
2 Introduction to Artificial Intelligence
3 Introduction to MATLAB
4 Basic applications on MATLAB and toolboxes
5 Fuzzy set theory and creation of fuzzy models
6 Fuzzy logic applications on MATLAB
7 Neurocomputing and creation of artificial neural network models
8 Applications of artificial neural networks on MATLAB
9 Midterm
10 Evolutionary computing and creation of genetic algorithm models
11 Applications of genetic algorithms on MATLAB
12 Based on artificial intelligence decision making and decision support systems
13 Fuzzy multi criteria decision making methods (Fuzzy AHP, Fuzzy DEMATEL)
14 Fuzzy multi criteria decision making methods (Fuzzy TOPSIS)
Resources
Course Notes
Course Resources

Hızıroğlu, A., Kiraz, A., Cebeci, H. İ., Taşkın, H., Selvi, İ. H., Codal, K. S., İpek, M., Şişci, Ş. M. “Esnek Hesaplama: İşletme ve Ekonomide Uygulamaları”, Çeviri Kitap, ISBN: 978-605-4735-80-8, 2017.

Kubat, C., MATLAB Yapay Zeka ve Mühendislik Uygulamaları, Pusula Yayıncılık ve İletişim, 2016.

Figueira, J., Greco, S., Ehrgott, M., Multi Criteria Decision Analysis State of the Art Surveys, Springer, International Series in Operations Research & Management Science, 2005.

Yıldırım, B., F., Önder, E., Çok Kriterli Karar Verme Yöntemleri, Dora Yayıncılık, 2016.

Order Program Outcomes Level of Contribution
1 2 3 4 5
1 The aim of the course is to reach the information in depth and in depth by conducting scientific research in the field of engineering, to evaluate, interpret and apply the information. X
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 50
1. Ödev 10
1. Performans Görevi (Uygulama) 50
Total 110
1. Yıl İçinin Başarıya 60
1. Final 40
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 2 32
Mid-terms 1 20 20
Performance Task (Application) 1 30 30
Final examination 1 20 20
Total Workload 150
Total Workload / 25 (Hours) 6
dersAKTSKredisi 6