ECTS - Natural Computing
Natural Computing (CMPE564) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Natural Computing | CMPE564 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Computer Engineering Elective Courses |
| Course Level | Ph.D. |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
|
| 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. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Problem solving by search, hill climbing, simulated annealing, artificial neural networks, genetic algorithms, swarm intelligence (including ant colony optimization and particle swarm optimization), artificial immune systems. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Introduction to Natural Computing | Chapter 1 & 2 (Course Book) |
| 2 | Introduction to Natural Computing | Chapter 1 & 2 (Course Book) |
| 3 | Problem Solving by Search; Hill Climbing; Simulated Annealing | Chapter 3 (Course Book) and Source #1 |
| 4 | Evolutionary Computing: Genetic Algorithms. | Chapter 3 (Course Book) and Source #1 |
| 5 | Evolutionary Computing: Genetic Algorithms. | Chapter 3 (Course Book) and Source #1 |
| 6 | Neurocomputing and Artificial Neural Networks | Chapter 4 (Course Book) and Source #2 |
| 7 | Neurocomputing and Artificial Neural Networks | Chapter 4 (Course Book) and Source #2 |
| 8 | Swarm Intelligence: Ant Colony Optimization | Chapter 5 (Course Book) and Source #3 |
| 9 | Swarm Intelligence: Ant Colony Optimization Chapter 5 (Course Book) and Source #3 | Chapter 5 (Course Book) |
| 10 | Swarm Intelligence: Particle Swarm Optimization | Chapter 5 (Course Book) |
| 11 | Swarm Intelligence: Particle Swarm Optimization | Chapter 5 (Course Book) |
| 12 | Artificial Immune Systems | Chapter 6 (Course Book) |
| 13 | Artificial Immune Systems | Chapter 6 (Course Book) |
| 14 | Artificial Immune Systems | Chapter 6 (Course Book) |
| 15 | Review | |
| 16 | Review |
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. |
|---|---|
| Other Sources | 2. S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, Prentice-Hall, 2003, ISBN: 0-13-790395-2. |
| 3. J. Hertz, A. Krogh and R.G. Palmer, Introduction to the Theory of Neural Computation, Addison-Wesley Publishing Company, 1991, ISBN: 0-201-50395-6. | |
| 4. M. Dorigo and T. Stützle, Ant Colony Optimization, MIT Press, 2004. ISBN: 0-262-04219-3. | |
| 5. Artificial Intelligence, Patrick H. Winston, Addison-Wesley, 1992. ISBN: 0-201-533774. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | 2 | 20 |
| Presentation | 1 | 20 |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 20 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 5 | 100 |
| Percentage of Semester Work | 60 |
|---|---|
| Percentage of Final Work | 40 |
| Total | 100 |
Course Category
| Core Courses | |
|---|---|
| Major Area Courses | |
| Supportive Courses | X |
| 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 | To become familiar with the state-of-the art and the literature in the software engineering research domain | X | ||||
| 2 | An ability to conduct world-class research in software engineering and publish scholarly articles in top conferences and journals in the area | |||||
| 3 | Be able to conduct quantitative and qualitative studies in software engineering | X | ||||
| 4 | Acquire skills needed to bridge software engineering academia and industry and to develop and apply scientific software engineering approaches to solve real-world problems | X | ||||
| 5 | An ability to access information in order to follow recent developments in science and technology and to perform scientific research or implement a project in the software engineering domain. | X | ||||
| 6 | An understanding of professional, legal, ethical and social issues and responsibilities related to Software Engineering. | |||||
| 7 | Skills in project and risk management, awareness about importance of entrepreneurship, innovation and long-term development, and recognition of international standards of excellence for software engineering practices standards and methodologies. | |||||
| 8 | An understanding about the impact of Software Engineering solutions in a global, environmental, societal and legal context while making decisions. | |||||
| 9 | Promote the development, adoption and sustained use of standards of excellence for software engineering practices. | |||||
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 | 3 | 48 |
| Presentation/Seminar Prepration | 1 | 5 | 5 |
| Project | |||
| Report | |||
| Homework Assignments | 2 | 5 | 10 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 10 | 10 |
| Prepration of Final Exams/Final Jury | 1 | 10 | 10 |
| Total Workload | 131 | ||