Department of Civil Engineering
Course Details
KTO KARATAY UNIVERSITY
Graduate Education Institute
Programme of Department of Civil Engineering
Course Details
Graduate Education Institute
Programme of Department of Civil Engineering
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 81011120 | Artificial Intelligence Applications in Civil Engineering | 2023 | Autumn | 1 | 3+0+0 | 7,5 | 7,5 |
| Course Type | Elective |
| Course Cycle | Master's (Second Cycle) (TQF-HE: Level 7 / QF-EHEA: Level 2 / EQF-LLL: Level 7) |
| Course Language | Turkish |
| Methods and Techniques | - |
| Mode of Delivery | Face to Face |
| Prerequisites | - |
| Coordinator | Asst. Prof. Vahdettin DEMİR |
| Instructor(s) | Asst. Prof. Vahdettin DEMİR |
| Instructor Assistant(s) | - |
Course Content
To realize Artificial Intelligence Applications in Civil Engineering by using different software and programs.
Objectives of the Course
Various methods such as artificial intelligence methods, artificial neural networks, fuzzy logic, heuristic regression methods, genetic algorithms, alternative to classical methods in solving engineering problems and the applications of these methods in solving engineering problems constitute the aim of the course.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | |
| Specialization / Field Courses | |
| Support Courses | |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Introduction Artificial Intelligence |
| 2 | Comparison criteria |
| 3 | ANN-Fuzzy Logic Methods |
| 4 | Heuristic Regression Methods |
| 5 | Deep learning |
| 6 | Optimization algorithms |
| 7 | Midterm |
| 8 | ANN-Fuzzy Logic Methods Applications |
| 9 | Heuristic Regression Methods Applications |
| 10 | Deep learning Applications |
| 11 | Optimization algorithms Applications |
| 12 | Application of Error Criteria |
| 13 | Interpretation of results and publication studies |
| 14 | Final exam |
Textbook or Material
| Resources | Scopus |
| Scopus |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 0 | 0 | 0 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 0 | 0 | 0 |
| Midterms | 0 | 0 | 0 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 0 | 0 | 0 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 0 | ||
| Total Work Load / 30 | 0 | ||
| Course ECTS Credits: | 0 | ||