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GRADUATE INSTITUTE of NATURAL and APPLIED SCIENCES / DEPARTMENT of CIVIL ENGINEERING
Doctorate
Course Catalog
www.ktu.edu.tr/fakulte/mmf/engineering.html
Phone: +90 0462 3772606
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GRADUATE INSTITUTE of NATURAL and APPLIED SCIENCES / DEPARTMENT of CIVIL ENGINEERING / Doctorate
Katalog Ana Sayfa
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INSL7640Artificial Intellig. Meth.in Water Resour.3+0+0ECTS:7.5
Year / SemesterSpring Semester
Level of CourseThird Cycle
Status Elective
DepartmentDEPARTMENT of CIVIL ENGINEERING
Prerequisites and co-requisitesNone
Mode of DeliveryFace to face
Contact Hours14 weeks - 3 hours of lectures per week
LecturerDr. Öğr. Üyesi Ergun UZLU
Co-Lecturer
Language of instructionTurkish
Professional practise ( internship ) None
 
The aim of the course:
Describe basic notions of artificial intelligence methods. Analysis the problem related to civil engineering using artificial neural networks.
 
Programme OutcomesCTPOTOA
Upon successful completion of the course, the students will be able to :
PO - 1 : Describe basic notions of artificial intelligence methods.
PO - 2 : Analysis the problem related to civil engineering using artificial neural networks.
CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome

 
Contents of the Course
Introducing of artificial intelligence methods. The fundamental concepts of feed forward back propagation artificial neural networks and Takagi?Sugeno (TS) fuzzy model. The applications of these methods for different problems of water resources engineering.
 
Course Syllabus
 WeekSubjectRelated Notes / Files
 Week 1INTRODUCE OF ARTIFICIAL INTELLIGENCE METHODS
 Week 2INTRODUCE OF GENETIC ALGORITHM
 Week 3EXAMINE OF APPLICATION OF GENETIC ALGORITHM IN CIVIL ENGINERING
 Week 4INTRODUCE OF FUZZY LOGIC
 Week 5EXAMINE OF APPLICATION OF FUZZY LOGIC IN CIVIL ENGINERING
 Week 6INTRODUCE OF ARTIFICIAL NEURAL NETWORK
 Week 7EXAMINE OF APPLICATION OF ARTIFICIAL NEURAL NETWORK IN CIVIL ENGINERING
 Week 8THE FUNDAMENTAL CONCEPTS OF FEED FORWARD BACK PROPAGATION ARTIFICIAL NEURAL NETWORKS
 Week 9First Midterm Exam
 Week 10THE FUNDAMENTAL CONCEPTS OF FEED FORWARD BACK PROPAGATION ARTIFICIAL NEURAL NETWORKS
 Week 11EXAMINE OF ARTIFICIAL NEURAL NETWORKS TOOLBOX IN MATLAB
 Week 12Second Midterm Exam
 Week 13DETERMINE OF DATA RELATED TO CIVIL ENGINEERING PROBLEM
 Week 14ANALYSIS THE PROBLEM IN CIVIL ENGINEERING USING ARTIFICIAL NEURAL NETWORKS TOOLBOX IN MATLAB
 Week 15ANALYSIS THE PROBLEM IN CIVIL ENGINEERING USİNG ARTIFICIAL NEURAL NETWORKS TOOLBOX IN MATLAB
 Week 16Final Exam
 
Textbook / Material
1Öztemel, E, Yapay Sinir Ağları, Papatya Yayıncılık, İstanbul, 2006, 232s.
2Şen, Z., Mühendislikte Bulanık (Fuzzy) Mantık ile Modelleme Prensipleri, Su Vakfı Yayınları, İstanbul, 2004, 191s.
 
Recommended Reading
1Haykin, S., Neural Networks: A Comprehensive Foundation (second ed.), Macmillan, 1994.
2Şen, Z., Yapay Sinir Ağları İlkeleri, Su Vakfı Yayınları, İstanbul, 2004, 183s.
3Demuth H., Beale M., and Hagan. M. Neural Network Toolbox 5 User’s Guide, The Math Works, 2007.
4Halıcı, U., Artificial Neural Network, Lecture Notes. http://vision1.eee.metu.edu.tr./~halici/543LectureNotes/543index.html 21 Nisan 2010.
5Yurtoğlu, H., Yapay Sinir Ağları Metodolojisi ile Öngörü Modellemesi: Bazı Makroekonomik Değişkenler İçin Türkiye Örneği, DPT Uzmanlık Tezi, DPT, Ankara, 2005.
 
Method of Assessment
Type of assessmentWeek NoDate

Duration (hours)Weight (%)
Mid-term exam 9 30
In-term studies (second mid-term exam) 12 20
End-of-term exam 16 50
 
Student Work Load and its Distribution
Type of workDuration (hours pw)

No of weeks / Number of activity

Hours in total per term
Yüz yüze eğitim 3 13 39
Sınıf dışı çalışma 3 13 39
Arasınav için hazırlık 8 1 8
Arasınav 1 2 2
Proje 5 1 5
Kısa sınav 1 2 2
Dönem sonu sınavı için hazırlık 8 1 8
Dönem sonu sınavı 2 1 2
Total work load105