| Course Type | Elective Course |
|---|
| Course Level | Master's Degree With Thesis |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 10 |
|---|
| Name of Lecturer(s) |
|
| Learning Outcomes |
At the end of this course, the students;
- Understand scientific and mathematical principles and apply them to the practice of engineering
- Gain an ability to use computer programs as tools for system design and analysis applications
- Gain an ability to apply the advanced principles of measurement, data analysis, and design of experiments
- Gain an ability to apply the system/process design levels to industrial engineering problems, including the consideration of different technical alternatives while bearing in mind cost, environmental concerns, safety, and other constraints.
- Gain an ability to analyze, measure, test, and evaluate an industrial engineering problem
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | None |
|---|
| Course Description | |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Introduction to neural Networks |
|
2nd Week |
Similarity between human brain and neural networks |
|
3rd Week |
Neural Network Patterns |
|
4th Week |
Neural Network Patterns |
|
5th Week |
Learning algorithms |
|
6th Week |
Learning algorithms |
|
7th Week |
ANN Architectures |
|
8th Week |
Midterm |
|
9th Week |
ANN Modelling |
|
10th Week |
ANN Verification Analysis |
|
11th Week |
Engineering Applications with ANN |
|
12th Week |
Engineering Applications with ANN |
|
13th Week |
Forecasting with ANN |
|
14th Week |
Optimization with ANN |
|
| Recommended or Required Reading | 1. Fausett, L. , Fundementals of Neural Networks, 1994.
2. Sağıroğlu, Ş., Beşdok, E., Erler, M., Mühendislikte Yapay Zeka Uygulamaları-1 Yapay Sinir Ağları, Ufuk Yayıncılık, 2003.
|
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Presentation
- Questions/Answers
- Project
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
30 |
| Project |
1 |
30 |
| Total(%) |
|
60 |
| Contribution of In-term Studies to Overall Grade(%) |
|
60 |
| Contribution of Final Examination to Overall Grade(%) |
|
40 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
2 |
2 |
| Preparation for Quiz |
|
|
|
| Individual or group work |
14 |
14 |
196 |
| Preparation for Final exam |
1 |
25 |
25 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
25 |
25 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
2 |
2 |
| Homework |
1 |
14 |
14 |
| Total Work Load | 306 |
| Total Work Load / 30 (h) | 10.2 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
