Ders Tanımı

Ders Kodu Yarıyıl T+U Saat Kredi AKTS
INTRODUCTION TO FUZZY LOGIC AND ARTIF. NEURAL NET. BSM 427 7 3 + 0 3 5
Ön Koşul Dersleri
Önerilen Seçmeli Dersler
Dersin Dili Türkçe
Dersin Seviyesi Lisans
Dersin Türü SECMELI
Dersin Koordinatörü Dr.Öğr.Üyesi MUHAMMED FATİH ADAK
Dersi Verenler Dr.Öğr.Üyesi MUHAMMED FATİH ADAK
Dersin Yardımcıları
Dersin Kategorisi
Dersin Amacı
The fuzzy logic has the capability of solving complex non-linear system using human intelligence and reasoning model. Neural Networks are used for modelling of the brain functions to solve complex non-linear system. This course presents basic knowledge about fuzzy logic, neural Networks and applications
Dersin İçeriği
Fuzzy sets. Membership functions. Fuzzy operations. T-norm, N- norm operator. Fuzzy Rules Fuzzification, defuzzification. Fuzzy inferrence. Mamdani fuzzy inference. Mamdani fuzzy inference applications. Sugenoi fuzzy inference and applications. Matlab fuzzy applications. The structure of the brain. Artificial Neuron. Perceptron. Multilayer neural networks. Learning. Back propagation algorithm. Momentum coefficient. Matlab neural network applications
Dersin Öğrenme Çıktıları Öğretim Yöntemleri Ölçme Yöntemleri
1 - Understand basic knowledge about fuzzy logic 1 - 2 - A - D -
2 - Understand basic knowledge about neural Networks 1 - 2 - A - D - F -
3 - Understand using the fuzzy logic and ANN for encountered problems 1 - 10 - A - B - C -
4 - Comrehend common fuzzy inference methods 1 - 2 - 10 - A - B - C -
5 - Comprehend sample fuzzy logic and ANN tools 1 - 2 - A - D -
Öğretim Yöntemleri: 1:Lecture 2:Question-Answer 10:Brain Storming
Ölçme Yöntemleri: A:Testing D:Project / Design F:Performance Task B:Oral Exam C:Homework
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