Mekatronik Mühendisliği

MCE 460 | Ders Tanıtım Bilgileri

Dersin Adı

Intelligent Systems

Kodu	Yarıyıl	Teori (saat/hafta)	Uygulama/Lab (saat/hafta)	Yerel Kredi	AKTS
MCE 460	FALL	3	0	3	6

Ön-Koşul(lar)	Yok
Dersin Dili	English
Dersin Türü	ELECTIVE_COURSE
Dersin Düzeyi	Lisans
Dersin Veriliş Şekli	Face-to-face
Dersin Öğretim Yöntem ve Teknikleri	Problem Solving Q&A Lecture / Presentation
Ulusal Meslek Sınıflandırma Kodu	-
Dersin Koordinatörü	Dr. Öğr. Üyesi Musa Özgün Güleç
Öğretim Eleman(lar)ı	Dr. Öğr. Üyesi Musa Özgün Güleç
Yardımcı(ları)	Araş. Gör. Rahime Alsanğur

Dersin Amacı

This course will provide Mechatronic engineering students with fundamental knowledge and skills in using intelligent systems. Students will learn how to use neural networks, fuzzy logic, and other nature-inspired algorithms. By examining case studies, they will gain experience in applications to real engineering problems.

Öğrenme Çıktıları

Bu dersi başarıyla tamamlayabilen öğrenciler;

Ad	Açıklama	PC Alt	* Katkı Düzeyi
Ad	Açıklama	PC Alt	1	2	3	4	5
LO1	Define intelligent systems.	1.5			X
LO2	Be able to design multi-layered artificial neural networks.	2		X
LO3	Be able to use fuzzy logic and neuro-fuzzy systems.	4		X
LO4	Compare optimization methods based on derivatives with optimization methods inspired by nature.	2		X
LO5	Will be able to suggest solutions to different problems with intelligent methods.	3.1				X

Ders Tanımı

Introduction to intelligent systems and nature inspired algorithms. Review for Optimization, modeling and control. Introduction to neural networks, back propagation learning rule, fuzzy set theory, fuzzy inference methods, fuzzy control, adaptive neuro-fuzzy inferencing system (ANFIS), genetic algorithms. Case studies with applications.

Dersin İlişkili Olduğu Sürdürülebilir Kalkınma Amaçları

Dersin Kategorisi	Temel Ders
	Uzmanlık/Alan Dersleri
	Destek Dersleri	X
	İletişim ve Yönetim Becerileri Dersleri
	Aktarılabilir Beceri Dersleri

HAFTALIK KONULAR VE İLGİLİ ÖN HAZIRLIK ÇALIŞMALARI

Hafta	Konular	Ön Hazırlık	Öğrenme Çıktısı
1	Introduction to intelligent systems	Textbook 1: Chapter 1	LO1
2	Introduction to artificial intelligence	Textbook 1: Chapter 1	LO1
3	Perceptron learning algorithms	Textbook 1: Chapter 2	LO2
4	Learning by back propagation of error	Textbook 1: Chapter 2	LO2
5	Artificial neural network (ANN) design and training	Textbook 1: Chapter 6	LO2
6	Use of neural networks for modeling and control	Textbook 1: Chapter 6	LO2
7	Introduction to fuzzy logic, fuzzy set theory	Textbook 1: Chapter 4	LO3
8	Midterm exam		-
9	Fuzzy composition and inference	Textbook 1: Chapter 4	LO3
10	Fuzzy control	Textbook 1: Chapter 4	LO3
11	Adaptive neuro-fuzzy inference system	Textbook 1: Chapter 8	LO3
12	Different combinations of neural networks and fuzzy systems	Textbook 1: Chapter 8	LO4
13	Particle swarm optimization and Genetic algorithm	Textbook 1: Chapter 7	LO5
14	Project presentations		-
15	Semester review		-
16	Final exam		-

Ders Kitabı	Artificial Intelligence: A Guide to Intelligent Systems - Michael Negnevitsky - Second Edition 2005 Addison-Wesley. ISBN 0 321 20466 2
Önerilen Okumalar/Materyaller	Ernest Davis - Douglas D. Edwards - David Forsyth - Nicholas J. Hay - Jitendra M. Malik - Vibhu Mittal - Mehran Sahami - Sebastian Thrun. Third Edition 2010 Editors: Stuart J. Russell and Peter Norvig. PRENTICE HALL.

DEĞERLENDİRME ÖLÇÜTLERİ

Yarıyıl Aktiviteleri	Sayı	Katkı Payı %	LO1	LO2	LO3	LO4	LO5
Ödev	1	10		X	X
Sunum / Jüri Önünde Sunum	1	5				X	X
Proje	1	15	X	X	X	X	X
Ara Sınav	1	30	X	X	X
Final Sınavı	1	40	X	X	X	X	X
Toplam	5	100

AKTS / İŞ YÜKÜ TABLOSU

Yarıyıl Aktiviteleri	Sayı	Süre (Saat)	İş Yükü
Katılım	-	-	-
Teorik Ders Saati	16	3	48
Laboratuvar / Uygulama Ders Saati	-	-	-
Sınıf Dışı Ders Çalışması	16	3	48
Arazi Çalışması	-	-	-
Küçük Sınav / Stüdyo Kritiği	-	-	-
Portfolyo	-	-	-
Ödev	1	12	12
Sunum / Jüri Önünde Sunum	1	12	12
Proje	1	20	20
Seminer/Çalıştay	-	-	-
Sözlü Sınav	-	-	-
Ara Sınavlar	1	15	15
Final Sınavı	1	25	25
		Toplam	180

DERSİN ÖĞRENME ÇIKTILARININ PROGRAM YETERLİLİKLERİ İLE İLİŞKİSİ

#	PC Alt	Program Yeterlilikleri / Çıktıları	* Katkı Düzeyi
#	PC Alt	Program Yeterlilikleri / Çıktıları	1	2	3	4	5
1	Engineering Knowledge: Knowledge of mathematics, science, basic engineering, computation, and related engineering discipline-specific topics; the ability to apply this knowledge to solve complex engineering problems.
	1	Mathematics
	2	Science
	3	Basic Engineering
	4	Computation
	5	Related engineering discipline-specific topics			LO1
	6	The ability to apply this knowledge to solve complex engineering problems
2	Problem Analysis: Ability to identify, formulate and analyze complex engineering problems using basic knowledge of science, mathematics and engineering, and considering the UN Sustainable Development Goals relevant to the problem being addressed.			LO2 LO4
3	Engineering Design: The ability to devise creative solutions to complex engineering problems; the ability to design complex systems, processes, devices or products to meet current and future needs, considering realistic constraints and conditions.
	1	Ability to design creative solutions to complex engineering problems				LO5
	2	Ability to design complex systems, processes, devices or products to meet current and future needs, considering realistic constraints and conditions
4	Use of Techniques and Tools: Ability to select and use appropriate techniques, resources, and modern engineering and computing tools, including estimation and modeling, for the analysis and solution of complex engineering problems, while recognizing their limitations.			LO3
5	Research and Investigation: Ability to use research methods to investigate complex engineering problems, including literature research, designing and conducting experiments, collecting data, and analyzing and interpreting results.
	1	Literature research for the study of complex engineering problems
	2	Designing experiments
	3	Ability to use research methods, including conducting experiments, collecting data. analyzing and interpreting results
6	Global Impact of Engineering Practices: Knowledge of the impacts of engineering practices on society, health and safety, economy, sustainability, and the environment, within the context of the UN Sustainable Development Goals; awareness of the legal implications of engineering solutions.
	1	Knowledge of the impacts of engineering practices on society, health and safety, economy, sustainability, and the environment, within the context of the UN Sustainable Development Goals
	2	Awareness of the legal implications of engineering solutions
7	Ethical Behavior: Acting in accordance with the principles of the engineering profession, knowledge about ethical responsibility; awareness of being impartial, without discrimination, and being inclusive of diversity.
	1	Acting in accordance with the principles of the engineering profession, knowledge about ethical responsibility ethical responsibility
	2	Awareness of being impartial and inclusive of diversity, without discriminating on any subject
8	Individual and Teamwork: Ability to work effectively, individually and as a team member or leader on interdisciplinary and multidisciplinary teams (face-to-face, remote or hybrid).
	1	Ability to work individually and within the discipline
	2	Ability to work effectively as a team member or leader in multidisciplinary teams (face-to-face, remote or hybrid)
9	Verbal and Written Communication: Taking into account the various differences of the target audience (such as education, language, profession) on technical issues.
	1	Ability to communicate verbally
	2	Ability to communicate effectively in writing
10	Project Management: Knowledge of business practices such as project management and economic feasibility analysis; awareness of entrepreneurship and innovation.
	1	Knowledge of business practices such as project management and economic feasibility analysis
	2	Awareness of entrepreneurship and innovation
11	Lifelong Learning: Lifelong learning skills that include being able to learn independently and continuously, adapting to new and developing technologies, and thinking questioningly about technological changes.