Ders Bilgileri

#### Ders Tanımı

Ders Kodu Yarıyıl T+U Saat Kredi AKTS
INTELLIGENT MODELING, OPTIMIZATION AND CONTROL ENM 602 0 3 + 0 3 6
 Dersin Dili Türkçe Dersin Seviyesi Doktora Dersin Türü SECMELI Dersin Koordinatörü Prof.Dr. HARUN TAŞKIN Dersi Verenler Dersin Yardımcıları Res. Assist. Ü. Atakan KAHRAMAN Dersin Kategorisi Dersin Amacı Giving a general skill and competency about intelligent techniques and ability of using these methods to model, optimize, and control processes to graduate students Dersin İçeriği Classical modeling, optimization and control, reasoning and inference under uncertainty, Fuzzy sets, operations, relationships, numbers, variables, and fuzzy logic, rule-based computations, Fuzzy-neural and evolutionary computations, Fuzzy modeling, problem solving with fuzzy sets, Methodology, Fuzzy optimization and control
 Dersin Öğrenme Çıktıları Öğretim Yöntemleri Ölçme Yöntemleri
 Öğretim Yöntemleri: Ölçme Yöntemleri:

#### Ders Akışı

Hafta Konular ÖnHazırlık
1 Classical Modeling, Optimization and Control
2 Reasoning and Inference Under Uncertainity
3 Fuzzy Sets and Operations
4 Fuzzy Relations and Numbers
5 Fuzzy Variables and Fuzzy Logic
6 Rule-Based Computations
7 Fuzzy Neurocomputations
8 Fuzzy Evolutionary Computations
9 Fuzzy Modeling I
10 Fuzzy Modeling II
11 Problem Solving with Fuzzy Sets: Introduction
12 Methodology
13 Fuzzy Optimization and Control
14 Case Studies (Traffic Intersection Control, Chemical Process Control, Manufacturing Control)

#### Kaynaklar

Ders Notu [1] Prof. Dr. Harun Taşkın, Intelligent Modelling Optimizatıon And Control Lecture Notes
Ders Kaynakları [2] ZADEH L.A., Fuzzy Sets, Information and Control, 8, (1965), 338-353
[3] LI, H., CHEN, C. L. P., HUANG, H.P., Fuzzy Neural Intelligent Systems: Mathematical Foundations and the Application in Engineering, CRC Pres, New York, 2000
[4] ROSS, T. J., Fuzzy Logic with Engineering Applications, Mc Graw Hill, New York, 1995
[5] WANG, L., X., A Course in Fuzzy Systems and Control, Prentice Hall, 1997
[6] TERANO T., ASAI, K., SUGENO, M., ASCHMANN, C., G., Fuzzy Systems Theory and Its Applications, Academic Press Inc., 1991
[7] PEDRYCZ, W., GOMIDE, F., An Introduction to Fuzzy Sets: Analysis and Design, A Bradford Book, 1998
[8] BAYKAL, N., BEYAN, T., Bulanık Mantık İlke ve Temelleri, Bıçaklar Kitabevi, 2004
[9] YEN, J., LANGARI, R., Fuzzy Logic: Intelligence, Control, and Information, Prentice Hall, 1998
[10] JAMSHIDI, M., Large-Scale Systems: Modeling, Control, and Fuzzy Logic, Prentice Hall, 1997
[11] JAMSHIDI, M., ZADEH, L.A., TITLI, A., Applications of Fuzzy Logic: Towards High Machine Intelligence Quotient Systems, Prentice Hall, 1997
[12] KARRAY, F.O., SILVA, C.W., Soft Computing and Intelligent Systems Design: Theory, Tools and Applications, Addison-Wesley, 2004

#### Dersin Program Çıktılarına Katkısı

No Program Öğrenme Çıktıları KatkıDüzeyi
1 2 3 4 5

#### Değerlendirme Sistemi

YARIYIL İÇİ ÇALIŞMALARI SIRA KATKI YÜZDESİ
AraSinav 1 40
KisaSinav 1 20
Odev 1 4
PerformansGoreviSeminer 1 20
Odev 2 4
Odev 3 4
Odev 4 4
Odev 5 4
Toplam 100
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 3 48
Mid-terms 1 7 7
Quiz 1 5 5
Assignment 5 5 25
Performance Task (Seminar) 1 5 5
Final examination 1 10 10
Toplam İş Yükü 148
Toplam İş Yükü /25(s) 5.92
Dersin AKTS Kredisi 5.92
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