Ders Bilgileri

#### Ders Tanımı

Ders Kodu Yarıyıl T+U Saat Kredi AKTS
SOFT COMPUTING METHODS AND APPLICATIONS ENM 555 0 3 + 0 3 6
 Dersin Dili Türkçe Dersin Seviyesi Yüksek Lisans Dersin Türü SECMELI Dersin Koordinatörü Dr.Öğr.Üyesi ALPER KİRAZ Dersi Verenler Dersin Yardımcıları Dersin Kategorisi Alanına Uygun Öğretim Dersin Amacı 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. Dersin İçeriği 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.
 Dersin Öğrenme Çıktıları Öğretim Yöntemleri Ölçme Yöntemleri 1 - Students know the principal concepts of soft computing 1 - 2 - 3 - A - B - C - 2 - Students are informed of methods of soft computing 1 - 2 - 3 - 4 - A - B - C - 3 - Students define and solve problems using soft computing methods 1 - 2 - 3 - 4 - 12 - 15 - A - B - C - 4 - Students are informed of decision making techniques 1 - 2 - 3 - A - B - C - 5 - Students Define and solve problems using decision making techniques 1 - 2 - 3 - 4 - 12 - 15 - A - B - C -
 Öğretim Yöntemleri: 1:Lecture 2:Question-Answer 3:Discussion 4:Drilland Practice 12:Case Study 15:Problem Solving Ölçme Yöntemleri: A:Testing B:Oral Exam C:Homework

#### Ders Akışı

Hafta Konular ÖnHazırlık
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)

#### Kaynaklar

Ders Notu
Ders Kaynakları

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.

#### Dersin Program Çıktılarına Katkısı

No Program Öğrenme Çıktıları KatkıDüzeyi
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

#### Değerlendirme Sistemi

YARIYIL İÇİ ÇALIŞMALARI SIRA KATKI YÜZDESİ
AraSinav 1 50
Odev 1 10
PerformansGoreviUygulama 1 50
Toplam 110
Yıliçinin Başarıya Oranı 60
Finalin Başarıya Oranı 40
Toplam 100

#### AKTS - İş Yükü

Etkinlik Sayısı Süresi(Saat) Toplam İş yükü(Saat)
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
Assignment 0 0 0
Performance Task (Application) 1 30 30
Final examination 1 20 20
Toplam İş Yükü 150
Toplam İş Yükü /25(s) 6
Dersin AKTS Kredisi 6
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