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SDÜ Education Information System Course Content
Programme
Graduate School of Natural and Applied Sciences Civil Engineering
Course Information
Course Unit Code
Course Unit Title
Credit Theoretic
Credit Pratic
Credit Lab/A
Credit Total
Credit Ects
Semester
01INS9614
NEURAL NETWORKS APPLICATIONS IN ENGINEERING
3.00
0.00
0.00
3.00
6.00
1
Course Information
Language of Instruction
Turkish
Type of Course Unit
Elective
Course Coordinator
Assistant Professor Dr. Kemal SAPLIOĞLU
Course Instructors
3-KEMAL SAPLIOĞLU
Course Assistants
3-KEMAL SAPLIOĞLU
Course Aims
Increasing the use of artificial neural networks in engineering
Course Goals
Artificial neural networks apply to engineering problems
Learning Outcomes of The Course Unit
Learning of neural networks
MATLAB-based model by the method of artificial neural networks to improve
Apply the method of artificial neural networks to engineering problems
Course Contents
Introduction to neural networks. Multi-layer artificial neural networks, training algorithms, modeling and engineering applications of the principles. Radial-based artificial neural networks, multi-layered artificial neural networks and applications according to their strengths and shortcomings. Examples of engineering application.
Prerequisities and Co-requisities Courses
 
Recommended Optional Programme Components
 
Mode Of Delivery
 
Level of Course Unit
 
Assessment Methods and Criteria
ECTS / Table Of Workload (Number of ECTS credits allocated)
Studies During Halfterm
Number
Co-Efficient
Activity
Number
Duration
Total
Visa
1
60
Course Duration (Excluding Exam Week)
14
3
42
Quiz
0
0
Time Of Studying Out Of Class
14
3
42
Homework
14
20
Homeworks
14
3
42
Attendance
1
10
Presentation
2
10
20
Application
1
10
Project
0
0
0
Lab
0
0
Lab Study
0
0
0
Project
0
0
Field Study
0
0
0
Workshop
0
0
Visas
1
10
10
Seminary
0
0
Finals
1
10
10
Field study
0
0
Workload Hour (30)
30
TOTAL
100
Total Work Charge / Hour
166
The ratio of the term to success
40
Course's ECTS Credit
6
The ratio of final to success
60
 
TOTAL
100
 
Recommended or Required Reading
Textbook
Artificial Neural Networks Applications lecture notes (prepared by Kemal SAPLIOĞLU)
Additional Resources
Çetin Elmas (2012), Yapay Zeka Uygulamaları, Yapay Sinir Ağları ? Bulanık Mantık?Genetik Algoritma, Ankara: Seçkin Yayinevi ISBN 9789750216961

Ercan Öztemel (2006), Yapay Sinir Ağları, Istanbul: Papatya ISBN 9789756797396

Yapay Sinir Ağları İlkeleri / Zekai Şen, Su Vakfı Yayınları
Material Sharing
Documents
 
Assignments
 
Exams
 
Additional Material
 
Planned Learning Activities and Teaching Methods
Lectures, Practical Courses, Presentation, Seminar, Project, Laboratory Applications (if necessary)
Work Placements
As with any other educational component, credits for work placements are only awarded when the learning outcomes have been achieved and assessed. If a work placement is part of organised mobility (such as Farabi and Erasmus), the Learning Agreement for the placement should indicate the number of credits to be awarded if the expected learning outcomes are achieved.
Program Learning Outcomes
No
Course's Contribution to Program
Contribution
1
An ability to design, conduct laboratory experiments and analyze and interpret data, in one of the major civil engineering areas
0