Faculty of Information Technology, BUT

Course details

Soft Computing

SFC Acad. year 2012/2013 Winter semester 5 credits

Current academic year

Soft computing covers non-traditional technologies or approaches for solving hard real-world problems. Content of course, in accordance with meaning of its name, is as follow: Tolerance of imprecision and uncertainty as the main attributes of soft computing theories. Neural networks. Fuzzy logic. Genetic algorithms. Probabilistic reasoning. Rough sets. Chaos.  Hybrid approaches (combinations of neural networks, fuzzy logic and genetic algorithms).

Guarantor

Language of instruction

Czech

Completion

Credit+Examination (written)

Time span

26 hrs lectures, 26 hrs projects

Assessment points

55 exam, 20 half-term test, 25 projects

Department

Lecturer

Instructor

Subject specific learning outcomes and competences

Students acquire knowledge of soft computing theories fundamentals and so they will be able to design program systems using approaches of these theories for solving various real-world problems.

Generic learning outcomes and competences

Students awake the importance of tolerance of imprecision and uncertainty for design of robust and low-cost intelligent machines.

Learning objectives

To give students knowledge of soft computing theories fundamentals, i.e. of fundamentals of non-traditional technologies and approaches to solving hard real-world problems, namely of fundamentals of artificial neural networks, fuzzy sets and fuzzy logic and genetic algorithms.

Study literature

  1. Aliev,R.A, Aliev,R.R.: Soft Computing and its Application, World Scientific Publishing Co. Pte. Ltd., 2001, ISBN 981-02-4700-1
  2. Mehrotra, K., Mohan, C., K., Ranka, S.: Elements of Artificial Neural Networks, The MIT Press, 1997, ISBN 0-262-13328-8
  3. Munakata, T.: Fundamentals of the New Artificial Intelligence, Springer-Verlag New York, Inc., 2008. ISBN 978-1-84628-838-8
  4. Russel,S., Norvig,P.: Artificial Intelligence, Prentice-Hall, Inc., 1995, ISBN 0-13-360124-2, second edition 2003, ISBN 0-13-080302-2

Fundamental literature

  1. Aliev,R.A, Aliev,R.R.: Soft Computing and its Application, World Scientific Publishing Co. Pte. Ltd., 2001, ISBN 981-02-4700-1
  2. Mehrotra, K., Mohan, C., K., Ranka, S.: Elements of Artificial Neural Networks, The MIT Press, 1997, ISBN 0-262-13328-8
  3. Munakata, T.: Fundamentals of the New Artificial Intelligence, Springer-Verlag New York, Inc., 1998. ISBN 0-387-98302-3
  4. Rutkowski, L.: Flexible Neuro-Fuzzy Systems, Kluwer Academic Publishers, 2004, ISBN 1-4020-8042-5
  5. Russel,S., Norvig,P.: Artificial Intelligence, Prentice-Hall, Inc., 1995, ISBN 0-13-360124-2, second edition 2003, ISBN 0-13-080302-2

Syllabus of lectures

  1. Introduction, Soft Computing concept explanation. Importance of tolerance of imprecision and uncertainty.
  2. Biological and artificial neuron, neural networks. Adaline, Perceptron. Madaline and BP (Back Propagation) neural networks.
  3. Adaptive feedforward multilayer networks.
  4. RBF and RCE neural networks. Topologic organized neural networks, competitive learning, Kohonen maps.
  5. CPN , LVQ, ART.
  6. Neural networks as associative memories (Hopfield, BAM, SDM).
  7. Solving optimization problems using neural networks. Stochastic neural networks, Boltzmann machine.
  8. Fuzzy sets, fuzzy logic and fuzzy inference.
  9. Genetic algorithms.
  10. Probabilistic reasoning.
  11. Rough sets.
  12. Chaos.
  13. Hybrid approaches (neural networks, fuzzy logic, genetic algorithms sets).

Syllabus - others, projects and individual work of students

Individual project - solving real-world problem (classification, optimization, association, controlling)

Progress assessment

  1. Mid-term written test
  2. Individual project

Course inclusion in study plans

  • Programme IT-MSC-2, field MBI, 2nd year of study, Compulsory
  • Programme IT-MSC-2, field MBS, MGM, MIS, MMI, MSK, any year of study, Elective
  • Programme IT-MSC-2, field MIN, 1st year of study, Compulsory
  • Programme IT-MSC-2, field MMM, any year of study, Compulsory-Elective group N
  • Programme IT-MSC-2, field MPV, 2nd year of study, Compulsory-Elective group B
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