COURSE UNIT TITLE

: FUZZY-LOGIC MODELING IN TRANSPORTATION ENGINEERING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CIE 5090 FUZZY-LOGIC MODELING IN TRANSPORTATION ENGINEERING ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR MUSTAFA ÖZUYSAL

Offered to

TRANSPORTATION ENGINEERING
TRANSPORTATION ENGINEERING
TRANSPORTATION ENGINEERING

Course Objective

In this course, it is aimed to provide knowledge about fuzzy sets and logic, membership and the description of membership functions, modeling process of fuzzy-logic approach, fuzzification, rule base construction, fuzzy inferences, defuzzification, the use of fuzzy-logic modeling softwares and applications in transportation engineering.

Learning Outcomes of the Course Unit

1   To analyze the variables that can t be stated by using classical numeric approaches in transportation engineering
2   To adapt a nonlinear modeling approach for transportation problems
3   To interpret the data structure used in transportation problems for different modeling purposes
4   To compare the efficiencies of linear and fuzzy-logic models
5   To classify and rebuild the model data according to the modeling purpose
6   To apply, analyze and present fuzzy-logic model on a transportation system problem

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Fuzziness concept, introduction, fuzziness and uncertainty
2 Fuzziness methods, fuzzy sets, membership rate, fuzzy systems, homework assignment
3 Membership functions, introduction to membership functions, components of the functions
4 Fuzzification, determination of membership rates
5 Classical and fuzzy sets, introduction to set logic, set descriptions and types, set components, population and empty sets, subset, graphical representations of the sets
6 Set operations, combined sets, intersecting sets, unmeshed sets, independent sets, included sets, adjunct sets, subtracted sets
7 Multiplication of sets, multiple set operations
8 Fuzzy mathematics, addition and subtraction of fuzzy numbers, generalization rule, multiplication and division of fuzzy numbers, homework assignment
9 Set relations, introductions to set relations, relation transition matrice, fuzzy relations, fuzzy tolerance and equivalence relations, value determination
10 Defuzzification, lambda sections of fuzzy sets, lambda sections in fuzzy relations, defuzzification operations
11 Fuzzy rules and systems, native language, linguistic hedges, mixing of fuzzy rules, rule based systems
12 Graphical inference methods, premise weighted systems and defuzzification
13 Applications, fuzzy logic model applications in transportation engineering
14 Homework submission and presentations

Recomended or Required Reading

Textbook(s): ŞEN, Z., Bulanık Mantık ve Modelleme Ilkeleri, 2001, Istanbul
Materials: Course presentations

Planned Learning Activities and Teaching Methods

The visual presentetions and presentetion slides.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 + ASG * 0.25 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 + ASG * 0.25 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

LO 1-5 will be evaluated by using mid-term and final exams.
LO 6 will be evaluated by using home-works and presentations.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Assoc.Prof.Dr. Serhan TANYEL (serhan.tanyel@deu.edu.tr)

Office Hours

It will be announced when the course schedule of the faculty is determined.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 4 56
Preparation for midterm exam 1 10 10
Preparation for final exam 1 15 15
Preparing assignments 2 25 50
Preparing presentations 2 10 20
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 197

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.1445353
LO.2453443
LO.354334
LO.45445433
LO.5344
LO.634543

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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