Ders Bilgileri

#### Ders Tanımı

Ders Kodu Yarıyıl T+U Saat Kredi AKTS
FUZZY SYSTEMS AND APPLICATIONS BSM 509 0 3 + 0 3 6
 Dersin Dili Türkçe Dersin Seviyesi Yüksek Lisans Dersin Türü SECMELI Dersin Koordinatörü Dr.Öğr.Üyesi SEÇKİN ARI Dersi Verenler Dr.Öğr.Üyesi SEÇKİN ARI Dersin Yardımcıları Dersin Kategorisi Dersin Amacı The fuzzy logic has the capability of solving complex non-linear system using human intelligence and reasoning model. This course presents basic knowledge about fuzzy logic, fuzzy inference methods, fuzzy logic modelling tools and applications. Dersin İçeriği Why fuzzy logic. Fuzzy sets. Membership functions. Fuzzy operations. T-norm, N- norm operators. Fuzzy arguments, extension principle. Fuzzy Rules Fuzzification, defuzzification. Fuzzy inference. Mamdani fuzzy inference. Mamdani fuzzy inference applications. Sugeno fuzzy inference and applications. Matlab fuzzy tool. Matlab fuzzy applications. Anfis and Anfis applications. Matlab Anfiis tool. Matlab Anfis applications. Student applications and paper studies.
 Dersin Öğrenme Çıktıları Öğretim Yöntemleri Ölçme Yöntemleri 1 - To understand basic knowledge about fuzzy logic 1 - 2 - A - D - 2 - To understand basic knowledge about adaptive fuzzy systems 1 - 2 - A - D - F - 3 - To understand using the fuzzy logic for encountered problems 1 - 2 - 10 - A - B - C - 4 - To learn common fuzzy inference methods. 1 - 15 - A - B - C - 5 - To learn sample fuzzy logic tools 1 - 2 - 14 - B - C - F - 6 - To obtain fuzzy system application capability 1 - 2 - 16 - C - D -
 Öğretim Yöntemleri: 1:Lecture 2:Question-Answer 10:Brain Storming 15:Problem Solving 14:Self Study 16:Project Based Learning Ölçme Yöntemleri: A:Testing D:Project / Design F:Performance Task B:Oral Exam C:Homework

#### Ders Akışı

Hafta Konular ÖnHazırlık
1 Why fuzzy logic.
2 Fuzzy sets. Membership functions
3 Fuzzy operations. T-norm, N- norm operators.
4 Fuzzy arguments, extension principle.
5 Fuzzy Rules Fuzzification, defuzzification. Fuzzy inference.
6 Mamdani fuzzy inference.
7 Mamdani fuzzy inference applications.
8 Sugeno fuzzy inference
9 Sugeno fuzzy inference applications
10 Matlab fuzzy tool. Matlab fuzzy applications.
11 Anfis and Anfis applications.
12 Matlab Anfiis tool. Matlab Anfis applications.
13 Student applications and paper studies.
14 Student applications and paper studies.

Ders Notu
Ders Kaynakları

#### Dersin Program Çıktılarına Katkısı

No Program Öğrenme Çıktıları KatkıDüzeyi
1 2 3 4 5
1 ability to complete and implement “limited or incomplete data” by using the scientific methods. X
2 ability to consolidate engineering problems, develop proper method(s) to solve and apply the innovative solutions to them X
3 ability to develop new and original ideas and method(s), to develop new innovative solutions at design of system, component or process X
4 gain comprehensive information on modern techniques, methods and their borders which are being applied to engineering X
5 ability to design and apply analytical, modelling and experimental based research, analyze and interpret the faced complex issues during the design and apply process X
6 gain high level ability to define the required information and data X
7 ability to work in multi-disciplinary teams and to take responsibility to define approaches for complex situations X
8 systematic and clear verbal or written transfer of the process and results of studies at national and international environments X
9 aware of social, scientific and ethical values guarding adequacy at all professional activities and at the stage of data collection, interpretation and announcement X
10 aware of new and developing application of profession and ability to analyze and study on those applications X
11 ability to interpret engineering application’s social and environmental dimensions and it’s compliance with the social environment X
12 ability to access wide and deep information with scientific researches in the field of Engineering, evaluate, interpret and implement the knowledge gained in his/her field of study X
13 ability to complete and implement “limited or incomplete data” by using the scientific methods. X
14 ability to consolidate engineering problems, develop proper method(s) to solve and apply the innovative solutions to them X
15 ability to develop new and original ideas and method(s), to develop new innovative solutions at design of system, component or process X
16 gain comprehensive information on modern techniques, methods and their borders which are being applied to engineering X
17 ability to design and apply analytical, modelling and experimental based research, analyze and interpret the faced complex issues during the design and apply process X
18 gain high level ability to define the required information and data X
19 ability to work in multi-disciplinary teams and to take responsibility to define approaches for complex situations X
20 systematic and clear verbal or written transfer of the process and results of studies at national and international environments X
21 aware of social, scientific and ethical values guarding adequacy at all professional activities and at the stage of data collection, interpretation and announcement X
22 aware of new and developing application of profession and ability to analyze and study on those applications X
23 ability to interpret engineering application’s social and environmental dimensions and it’s compliance with the social environment X

#### Değerlendirme Sistemi

YARIYIL İÇİ ÇALIŞMALARI SIRA KATKI YÜZDESİ
AraSinav 1 50
KisaSinav 1 5
Odev 1 40
KisaSinav 2 5
Toplam 100
Yıliçinin Başarıya Oranı 50
Finalin Başarıya Oranı 50
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 25 25
Final examination 1 20 20
Toplam İş Yükü 141
Toplam İş Yükü /25(s) 5.64
Dersin AKTS Kredisi 5.64
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