ECTS - Advanced Natural Computing
Advanced Natural Computing (MDES662) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
---|---|---|---|---|---|---|---|
Advanced Natural Computing | MDES662 | Elective Courses | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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N/A |
Course Language | English |
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Course Type | Elective Courses Taken From Other Departments |
Course Level | Ph.D. |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture. |
Course Lecturer(s) |
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Course Objectives | The objective of this course is to teach different nature inspired computing techniques; to gain an insight about how to solve real-life practical computing and optimization problems; to gain experience about Simulation and Emulation of Natural Phenomena in Computers, and to become familiar with new natural medium usage in computing. |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Evolutionary computing, ant colony optimization, particle swarm optimization, artificial bee colonies, cellular automata, L-systems, artificial life, DNA computing. |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | Introduction to Natural Computing | Chapter 1 & 2 (Course Book) |
2 | Evolutionary Computing | Chapter 3 (Course Book) and Source #1 |
3 | Evolutionary Computing | Chapter 3 (Course Book) and Source #1 |
4 | Swarm Intelligence: Ant Colony Optimization | Chapter 5 (Course Book) and Source #2 |
5 | Swarm Intelligence: Ant Colony Optimization | Chapter 5 (Course Book) and Source #2 |
6 | Swarm Intelligence: Particle Swarm Optimization | Chapter 5 (Course Book) and Source #5 |
7 | Swarm Intelligence: Particle Swarm Optimization | Chapter 5 (Course Book) and Source #5 |
8 | Swarm Intelligence: Artificial Bee Colony Algorithm | Source #4 |
9 | Simulation and Emulation of Natural Phenomena: Cellular Automata | Chapter 7.3 (Course Book) |
10 | Simulation and Emulation of Natural Phenomena: L-Systems | Chapter 7.4 (Course Book) |
11 | Artificial Life | Chapter 8 (Course Book) |
12 | Artificial Life | Chapter 8 (Course Book) |
13 | Computing on New Medium: DNA Computing | Chapter 9 (Course Book) |
14 | Computing on New Medium: DNA Computing | Chapter 9 (Course Book) |
15 | Overall review | - |
16 | Final exam | - |
Sources
Course Book | 1. Leandro Nunes de Castro, Fundamentals of Natural Computing: Basic Concepts, Algorithms and Applications, Chapman & Hall/CRC, 2006, ISBN 1-58488-643-9. |
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Other Sources | 2. S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, Prentice-Hall, 2003 |
3. M. Dorigo and T. Stützle, Ant Colony Optimization, MIT Press, 2004. | |
4. Artificial Intelligence, Patrick H. Winston, Addison-Wesley, 1992. | |
5. http://mf.erciyes.edu.tr/abc/publ.htm | |
6. http://www.swarmintelligence.org |
Evaluation System
Requirements | Number | Percentage of Grade |
---|---|---|
Attendance/Participation | - | - |
Laboratory | - | - |
Application | - | - |
Field Work | - | - |
Special Course Internship | - | - |
Quizzes/Studio Critics | - | - |
Homework Assignments | 1 | 10 |
Presentation | 1 | 10 |
Project | 1 | 30 |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 1 | 20 |
Final Exam/Final Jury | 1 | 30 |
Toplam | 5 | 100 |
Percentage of Semester Work | 70 |
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Percentage of Final Work | 30 |
Total | 100 |
Course Category
Core Courses | |
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Major Area Courses | X |
Supportive Courses | |
Media and Managment Skills Courses | |
Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
# | Program Qualifications / Competencies | Level of Contribution | ||||
---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | ||
1 | Ability to carry out advanced research activities, both individual and as a member of a team | |||||
2 | Ability to evaluate research topics and comment with scientific reasoning | |||||
3 | Ability to initiate and create new methodologies, implement them on novel research areas and topics | |||||
4 | Ability to produce experimental and/or analytical data in systematic manner, discuss and evaluate data to lead scintific conclusions | |||||
5 | Ability to apply scientific philosophy on analysis, modelling and design of engineering systems | |||||
6 | Ability to synthesis available knowledge on his/her domain to initiate, to carry, complete and present novel research at international level | |||||
7 | Contribute scientific and technological advancements on engineering domain of his/her interest area | |||||
8 | Contribute industrial and scientific advancements to improve the society through research activities |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
---|---|---|---|
Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
Laboratory | |||
Application | |||
Special Course Internship | |||
Field Work | |||
Study Hours Out of Class | 16 | 1 | 16 |
Presentation/Seminar Prepration | 1 | 15 | 15 |
Project | 1 | 25 | 25 |
Report | |||
Homework Assignments | 1 | 15 | 15 |
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 1 | 8 | 8 |
Prepration of Final Exams/Final Jury | 1 | 10 | 10 |
Total Workload | 137 |