Course Name Code Semester T+U Hours Credit ECTS
Artificial Intelligence Applications In Mechatronic Engineering MEK 523 0 3 + 0 3 6
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level yuksek_lisans
Course Type Optional
Course Coordinator Prof.Dr. RAŞİT KÖKER
Course Lecturers
Course Assistants
Course Category Field Proper Education
Course Objective Students learn the basic principles of artificial intelligence and their applications to engineering problems as well as their in depth analyzes. Students learn the basic principles of fuzzy logical, experts systems and ANN in addition to their applications engineering.
Course Content Definition of artificial intelligence, The basic concepts and techniques, Expert Systems and engineering applications, Fuzzy logic and engineering applications, Genetic algorithms and application examples, Artificial neural networks: structure and basic elements of artificial neural networks, Engineering applications of artificial neural networks, Hybrid techniques (fuzzy-neural, fuzzy-genetic, etc.)
# Course Learning Outcomes Teaching Methods Assessment Methods
1 Definitions of artificial intelligence, basic concepts and techniques Lecture, Question-Answer, Self Study, Testing, Homework,
2 Experts systems ? application to mechatronics engineering Lecture, Question-Answer, Self Study, Testing, Homework,
3 Solutions to engineering problems using ANN Lecture, Question-Answer, Self Study, Testing, Homework, Performance Task,
4 Mechatronics engineering Applications by fuzzy logic Lecture, Question-Answer, Self Study, Testing, Homework, Performance Task,
5 Engineering applications by genetic algorithms Lecture, Question-Answer, Self Study, Testing, Homework, Performance Task,
Week Course Topics Preliminary Preparation
1 İntroduction to Artificial intelligence technology
2 Expert Systems and engineering applications
3 Artificial Neural Networks: structure and basic elements of artificial neural networks
4 Multilayer Perceptrons - Backpropagation
5 Engineering applications of artificial neural networks
6 Engineering applications of artificial neural networks
7 Fuzzy Logic:The basic concepts
8 Features of Fuzzy logic
9 Fuzzy Logic and engineering applications
10 Basic theorem of genetic algorithm
11 Genetic algorithms and application examples
12 Midterm Exam
13 Presentations of student projects
14 Presentations of student projects
Resources
Course Notes
Course Resources 1. Yapay Zeka, Vasif Nabiyev, Seçkin Yayınevi, 2010.
2. Mühendislikte yapay zeka uygulamaları, Ş.Sağıroğlu, E.Beşdok, M.Erler, Ufuk Yayınevi, 2003.
3. Neural Network Design, M. Hagan, 2002
4. .Fuzzy Logic and control, M. Jamshidi, Prentice Hall, 1993.
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 Ability to access wide and deep information with scientific researches in the field of Engineering, evaluate, interpret and implement the knowledge gained in his/her field of study X
2 Develop new strategic approach and produce solutions by taking responsibility in unexpected and complicated situations in mechatronic engineering X
3 Aware of social, scientific and ethical values guarding adequacy at all professional activities and at the stage of data collection, interpretation, and announcement X
4 Develop and use data processing and communication technologies together with the machine, electronic and computer software-hardware knowledge required by the field of mechatronic engineering expertise
5 Ability to complete and implement "limited or incomplete data" by using the scientific methods. X
6 Ability to consolidate engineering problems, develop proper method(s) to solve and apply the innovative solutions to them X
7 Ability to develop new and original ideas and method(s), to develop new innovative solutions at design of system, component or process
8 Ability to design and apply analytical, modeling and experimental based research, analyze and interpret the faced complex issues during the design and apply process X
9 Gain high level ability to define the required information and data X
10 Aware of new and developing application of profession and ability to analyze and study on those applications
11 Ability to interpret engineering applications social and environmental dimensions and it´s compliance with the social environment
12 At least be capable of oral and written communication in a foreign language
13 Ability to work in multi-disciplinary teams and to take responsibility to define approaches for complex situations
14 Systematic and clear verbal or written transfer of the process and results of studies at national and international environments X
15 Gain comprehensive information on modern techniques, methods and their borders which are being applied to engineering X
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 55
1. Ödev 30
1. Performans Görevi (Uygulama) 15
Total 100
1. Yıl İçinin Başarıya 60
1. Final 40
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 4 64
Mid-terms 1 6 6
Assignment 1 10 10
Performance Task (Application) 1 10 10
Final examination 1 8 8
Total Workload 146
Total Workload / 25 (Hours) 5.84
dersAKTSKredisi 6