541-0888/01 – Expert Systems in GIS (ES_GIS_D)

Gurantor departmentDepartment of Geological EngineeringCredits0
Subject guarantordoc. RNDr. František Staněk, Ph.D.Subject version guarantordoc. RNDr. František Staněk, Ph.D.
Study levelpostgraduateRequirementOptional
YearSemesterwinter + summer
Study languageCzech
Year of introduction2001/2002Year of cancellation2010/2011
Intended for the facultiesHGFIntended for study typesDoctoral
Instruction secured by
LoginNameTuitorTeacher giving lectures
STA22 doc. RNDr. František Staněk, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 0+0
Part-time Credit and Examination 0+0

Subject aims expressed by acquired skills and competences

The first part of this course is dedicated to solving expert problems. These problems can arise from other courses as well as from practice. The main emphasis lays in explanation of fundamental principles of problem solving strategies and of their general properties. The students learn how to decide which procedure is a suitable tool for solving a specific problem. An important ingredient of the course is algorithmic implementation in PROLOG language. The students learn how to use existing Expert Systems, too. The second part of the course deals with basic types of Artificial Neural Networks and with the way in which to understand these networks from both theoretical and practical points of view. The students are taught how to use these general methods to solve the problems arising from other courses of their study and from practice.

Teaching methods

Individual consultations
Project work


Introduction to Artificial Intelligence (AI). Languages of AI. Introduction to PROLOG. Problem solving strategies. Expert System (ES). Describe the characteristics, features, structures, limitations, and benefits of ES. Describe the various methods of knowledge representation and build simple rule-based knowledge bases. Describe the various methods of inference. Conduct manual backward and forward chaining inferences. Artificial Neural Networks. The most common models like Backpropagation multilayered, Recurrent multilayered, Kohonen, Counterpropagation, Hopfield, BAM and ART nets are introduced. Object-oriented model of all mentioned types of neural networks. Expert System and Neural Network. Applications of Neural Network in Imaging Processing.

Compulsory literature:

Giarratano, J., Riley, G.: Expert Systems: Principles and Programming. 4th ed. Boston: Thomson Course Technology, 2005, 842 s.

Recommended literature:

Nilsson, N.J.: Artificial Intelligence: A New Synthesis. Morgan Kaufmann, 1998

Way of continuous check of knowledge in the course of semester


Other requirements


Subject has no prerequisities.


Subject has no co-requisities.

Subject syllabus:

Jazyky umělé inteligence. Metody hledání řešení. Charakteristika, vlastnosti a architektura expertních systémů. Reprezentace znalostí. Pravidla a inferenční sítě. Řídící mechanismy. Neuronové sítě. Modely neuronů. Vícevrstvé topologie. Metody Backpropagation. Parametrická Backpropagation. Implementace neuronů s intervalovým stavem excitace. Zobecnělá metoda Backpropagation pro neuronové sítě s neurčitostí. Rekurentní vícevrstvé neuronové sítě. Kohonenovo učení a samoorganizující se neuronové sítě. LVQ modely a counter-propagation Hopfieldovy sítě. Boltzmannův stroj. Dvousměrná asociativní paměť. Adaptivní rezonanční teorie. Objektově-orientovaný přístup k modelování neuronových sítí. Expertní systémy využívající neurovné sítě. Neuronové zpracování obrazové informace.

Conditions for subject completion

Full-time form (validity from: 1960/1961 Summer semester, validity until: 2012/2013 Summer semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Exercises evaluation and Examination Credit and Examination 100 (145) 51 3
        Examination Examination 100  0 3
        Exercises evaluation Credit 45  0 3
Mandatory attendence participation:

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Conditions for subject completion and attendance at the exercises within ISP:

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Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2009/2010 (P3646) Geodesy and Cartography (3602V002) Geoinformatics P Czech Ostrava Optional study plan
2009/2010 (P3646) Geodesy and Cartography (3602V002) Geoinformatics K Czech Ostrava Optional study plan
2008/2009 (P3646) Geodesy and Cartography (3602V002) Geoinformatics K Czech Ostrava Optional study plan
2008/2009 (P3646) Geodesy and Cartography (3602V002) Geoinformatics P Czech Ostrava Optional study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

Assessment of instruction

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