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GRADUATE INSTITUTE of NATURAL and APPLIED SCIENCES / DEPARTMENT of STATISTICS and COMPUTER SCIENCES
Statistics-Masters with Thesis
Course Catalog
https://www.ktu.edu.tr/fbeistatistik
Phone: +90 0462 (0462) 3773112
FBE
GRADUATE INSTITUTE of NATURAL and APPLIED SCIENCES / DEPARTMENT of STATISTICS and COMPUTER SCIENCES / Statistics-Masters with Thesis
Katalog Ana Sayfa
  Katalog Ana Sayfa  KTÜ Ana Sayfa   Katalog Ana Sayfa
 
 
ISTL5035Swarm Intelligence3+0+0ECTS:7.5
Year / SemesterSpring Semester
Level of CourseSecond Cycle
Status Elective
DepartmentDEPARTMENT of STATISTICS and COMPUTER SCIENCES
Prerequisites and co-requisitesNone
Mode of Delivery
Contact Hours14 weeks - 3 hours of lectures per week
Lecturer--
Co-Lecturer-
Language of instructionTurkish
Professional practise ( internship ) None
 
The aim of the course:
This course aims to introduce the basic principles and algorithms of swarm intelligence to the students and to use swarm intelligence based algorithms for solving continuous and discrete optimization problems.
 
Programme OutcomesCTPOTOA
Upon successful completion of the course, the students will be able to :
PO - 1 : Understand the concept and principles of swarm intelligence
PO - 2 : Learn and use swarm intelligence based algorithms
PO - 3 : Solve the problems using swarm intelligence based algorithms
PO - 4 : Apply swarm intelligence based algorithms to real problems
CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome

 
Contents of the Course
The concept and principles of swarm intelligence, swarm intelligence based algorithm, ant colony algorithm, particle swarm optimization, artificial bee colony algorithm, firefly algorithm, cuckoo search algorithm, bat algorithm
 
Course Syllabus
 WeekSubjectRelated Notes / Files
 Week 1The concept and principles of swarm intelligence
 Week 2Swarm intelligence based algorithm
 Week 3Ant colony algorithm
 Week 4Ant colony algorithm
 Week 5Particle swarm optimization
 Week 6Particle swarm optimization
 Week 7Artificial bee colony algorithm
 Week 8Artificial bee colony algorithm
 Week 9Midterm exam
 Week 10Firefly algorithm
 Week 11Firefly algorithm
 Week 12Cuckoo search algorithm
 Week 13Cuckoo search algorithm
 Week 14Bat algorithm
 Week 15Bat algorithm
 Week 16Final exam
 
Textbook / Material
 
Recommended Reading
 
Method of Assessment
Type of assessmentWeek NoDate

Duration (hours)Weight (%)
Mid-term exam 9 21/11/2018 2 50
End-of-term exam 16 09/01/2019 2 50
 
Student Work Load and its Distribution
Type of workDuration (hours pw)

No of weeks / Number of activity

Hours in total per term
Yüz yüze eğitim 3 1 3
Arasınav 2 2 4
Dönem sonu sınavı 2 1 2
Total work load9