1	Course Title:	MODELING TECHNICS IN AGRICULTURAL MACHINERY
2	Course Code:	BSM6017
3	Type of Course:	Optional
4	Level of Course:	Third Cycle
5	Year of Study:	1
6	Semester:	1
7	ECTS Credits Allocated:	6
8	Theoretical (hour/week):	2
9	Practice (hour/week) :	2
10	Laboratory (hour/week) :	0
11	Prerequisites:	None
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Prof. Dr. ALİ VARDAR
16	Course Lecturers:	YOK
17	Contactinformation of the Course Coordinator:	e-posta: dravardar@uludag.edu.tr Telefon: 0 224 2941605 Adres: Bursa Uludağ Üniversitesi, Ziraat Fakültesi, Biyosistem Mühendisliği Bölümü, Görükle Kampüsü, 16059, Nilüfer/BURSA
18	Website:
19	Objective of the Course:	The aim of the course; To provide students with basic information on scientific research techniques, mathematical modeling, three-dimensional basic design, stress analysis.
20	Contribution of the Course to Professional Development	It contributes to the ability of the student to make modeling related to his field.

21

Learning Outcomes:

1 Understanding the importance of the concept of mathematical modeling; 2 Ability to use mathematical modeling techniques in problem solving;

22	Course Content:

Week	Theoretical	Practical
1	introduction	introduction
2	Scientific research techniques	Application examples
3	Thought and model	Application examples
4	Mathematical models and rational logic models	Application examples
5	Differential models	Application examples
6	Experimental modeling principles	Application examples
7	Rational-experimental modeling	Application examples
8	Finite small range (numerical) modeling	Application examples
9	An overview	An overview
10	Modeling with probability methods and churn models	Application examples
11	Modeling with artificial neural networks method	Application examples
12	Modeling with fuzzy logic method	Application examples
13	Optimization	Application examples
14	An overview	An overview

23	Textbooks, References and/or Other Materials:	Şen, Z., 2002. Bilimsel düşünce ve matematik modelleme ilkeleri, Su Vakfı Yayınları, İstanbul. Şen, Z., 2009. Temiz enerji kaynakları ve modelleme ilkeleri, Su Vakfı Yayınları, İstanbul. Elmas, Ç., 2007. Yapay zeka uygulamaları, Seçkin yayıncılık, Ankara. Şen, Z., 2009. Bulanık mantık ilkeleri ve modelleme, Su Vakfı Yayınları, İstanbul. Tülücü, K., 1997. Optimizasyon, Çukurova Üniversitesi Ziraat Fakültesi Genel Yayın No: 189, Adana.
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	0	0
Quiz	0	0
Homeworks, Performances	0	0
Final Exam	1	100
Total	1	100
Contribution of Term (Year) Learning Activities to Success Grade		0
Contribution of Final Exam to Success Grade		100
Total		100
Measurement and Evaluation Techniques Used in the Course	The effect of the final exam on the course-passing grade is 100%.
Information	If the number of students is over 20, relative evaluation is applied, if less than 20 students, absolute evaluation is applied.

25

ECTS / WORK LOAD TABLE

Activites	NUMBER	TIME [Hour]	Total WorkLoad [Hour]
Theoretical	14	2	28
Practicals/Labs	14	2	28
Self Study and Preparation	14	3	42
Homeworks, Performances	0	50	50
Projects	0	0	0
Field Studies	0	0	0
Midtermexams	0	0	0
Others	0	0	0
Final Exams	1	36	36
Total WorkLoad			184
Total workload/ 30 hr			6,13
ECTS Credit of the Course			6

26	CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
PQ1 PQ2 PQ3 PQ4 PQ5 PQ6 PQ7 PQ8 PQ9 PQ10 PQ11 PQ12 LO1 4 4 4 4 4 3 3 4 3 3 1 4 LO2 4 4 4 3 4 3 3 4 3 3 4 4

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High