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477525S Computational intelligence in automation, 5 ECTS cr 
Code 477525S  Validity 01.08.2015 -
Name Computational intelligence in automation  Abbreviation Computational i 
Scope5 ECTS cr   
TypeAdvanced Studies Discipline4357 Process and Environmental Engineering 
  Grading1 - 5, pass, fail 
Unit Field of Process and Environmental Engineering 

Aki Sorsa 

ECTS Credits 

5 ECTS / 135 hours of work

Language of instruction 

Finnish and English


Implementation in the spring term, on the 3rd period. Recommended for 4th year students (first M.Sc. year)

Learning outcomes 

After the course the student is capable of explaining the concepts of intelligent systems and operation principles of fuzzy set systems, neural networks, neuro-fuzzy systems and evolutionary computation. The student has skills to construct and tune fuzzy models in Matlab-Simulink environment and to explain the operation of these models. The student is able to explain in an integrating way the principle concepts of neural computing and construct neural network models in Matlab-Simulink environment. The student is able to explain the operation principles of genetic algorithms and to use them in tuning of fuzzy set systems and neural network models.


Fuzzy logic and fuzzy set systems, fuzzy calculus, fuzzy modelling and control, neural computation, neuro-fuzzy methods and evolutionary computation.

Mode of delivery 

Tuition is implemented mainly as face-to-face teaching.

Learning activities and teaching methods 

The amount of guided teaching is 40 hrs including lectures, exercises and a possible seminar presentation. As a self-study, students carry out homework, case study and seminar presentation preparation.

Target group 

M.Sc. students in process and environmental engineering, machine engineering, computer engineering and industrial engineering and management.

Prerequisites and co-requisites 

No specific prerequisites, but skills for simulation, and programming in Matlab are a benefit.

See "Recommended optional programme components" below.

Recommended optional programme components 

Courses Simulation, and Programming in Matlab reinforce abilities for the exercises and the case study.

Recommended or required reading 

Lecture notes and materials. Other literature.

Assessment methods and criteria 

This course uses continuous assessment that includes homework, classroom or home exams, case study and a possible seminar presentation.

Read more about the course assessment and grading systems of the University of Oulu at


The course unit uses a numerical grading scale 1-5. In the numerical scale zero stands for a fail.

Person responsible 

Aki Sorsa

Working life cooperation 



Current and future instruction
Functions Name Type ECTS cr Teacher Schedule
registration period has ended Computational intelligence in automation  Course  Aki Sorsa  01.06.21 -31.08.21

Future examinations
No examinations in WebOodi