Title:  Soft Computing 

Code:  SFC 

Ac.Year:  2009/2010 

Term:  Winter 

Curriculums:  

Language:  Czech, English 

Private info:  http://www.fit.vutbr.cz/study/courses/SFC/private/ 

Credits:  5 

Completion:  examination (written) 

Type of instruction:  Hour/sem  Lectures  Sem. Exercises  Lab. exercises  Comp. exercises  Other 

Hours:  26  0  0  0  26 

 Examination  Tests  Exercises  Laboratories  Other 

Points:  55  20  0  0  25 



Guarantee:  Zbořil František V., doc. Ing., CSc., DITS 

Lecturer:  Zbořil František V., doc. Ing., CSc., DITS 
Instructor:  Rozman Jaroslav, Ing., Ph.D., DITS 

Faculty:  Faculty of Information Technology BUT 

Department:  Department of Intelligent Systems FIT BUT 

Substitute for:  

 Learning objectives: 

  To give students knowledge of soft computing theories fundamentals, i.e. of fundamentals of nontraditional technologies and approaches to solving hard realworld problems, namely of fundamentals of artificial neural networks, fuzzy sets and fuzzy logic and genetic algorithms.  Description: 

  Soft computing covers nontraditional technologies or approaches for solving hard realworld 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).  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 realworld problems.  Generic learning outcomes and competences: 

  Students awake the importance of tolerance of imprecision and uncertainty for design of robust and lowcost intelligent machines.  Syllabus of lectures: 



 Introduction, Soft Computing concept explanation. Importance of tolerance of imprecision and uncertainty.
 Biological and artificial neuron, neural networks. Adaline, Perceptron. Madaline and BP (Back Propagation) neural networks.
 Adaptive feedforward multilayer networks.
 RBF and RCE neural networks. Topologic organized neural networks, competitive learning, Kohonen maps.
 CPN , LVQ, ART, Neocognitron neural networks
 Neural networks as associative memories (Hopfield, BAM, SDM).
 Solving optimization problems using neural networks. Stochastic neural networks, Boltzmann machine.
 Fuzzy sets, fuzzy logic and fuzzy inference.
 Genetic algorithms.
 Probabilistic reasoning.
 Rough sets.
 Chaos.
 Hybrid approaches (neural networks, fuzzy logic, genetic algorithms sets).
 Syllabus  others, projects and individual work of students: 

 Individual project  solving realworld problem (classification, optimization, association, controlling)  Fundamental literature: 


 Aliev,R.A, Aliev,R.R.: Soft Computing and its Application, World Scientific Publishing Co. Pte. Ltd., 2001, ISBN 9810247001
 Cordón, O., Herrera, F., Hoffman, F., Magdalena, L.: Genetic Fuzzy systems, World Scientific Publishing Co. Pte. Ltd., 2001, ISBN 9810240163
 Kecman, V.: Learning and Soft Computing, The MIT Press, 2001, ISBN 0262112558
 Mehrotra, K., Mohan, C., K., Ranka, S.: Elements of Artificial Neural Networks, The MIT Press, 1997, ISBN 0262133288
 Munakata, T.: Fundamentals of the New Artificial Intelligence, SpringerVerlag New York, Inc., 1998. ISBN 0387983023
 Rutkowski, L.: Flexible NeuroFuzzy Systems, Kluwer Academic Publishers, 2004, ISBN: 1402080425
 Zaknih, A.: Neural Networks for Intelligent Signal Processing, World Scientific Publishing Co. Pte. Ltd., 2003, ISBN 9812383050
 Study literature: 


 Aliev,R.A, Aliev,R.R.: Soft Computing and its Application, World Scientific Publishing Co. Pte. Ltd., 2001, ISBN 9810247001
 Mehrotra, K., Mohan, C., K., Ranka, S.: Elements of Artificial Neural Networks, The MIT Press, 1997, ISBN 0262133288
 Munakata, T.: Fundamentals of the New Artificial Intelligence, SpringerVerlag New York, Inc., 2008. ISBN 9781846288388
 Progress assessment: 

 
 Midterm written test
 Individual project
 
