541-0044/02 – Expert Systems in GIS (ESGIS)

Gurantor departmentDepartment of Geological EngineeringCredits5
Subject guarantordoc. RNDr. František Staněk, Ph.D.Subject version guarantordoc. RNDr. František Staněk, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Year1Semestersummer
Study languageCzech
Year of introduction1999/2000Year of cancellation2009/2010
Intended for the facultiesHGFIntended for study typesFollow-up Master
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 2+2
Combined Credit and Examination 12+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

Lectures
Tutorials

Summary

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. 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., Brooks Cole, 2004 Nilsson, N.J.: Artificial Intelligence: A New Synthesis. Morgan Kaufmann, 1998

Recommended literature:

Way of continuous check of knowledge in the course of semester

E-learning

Další požadavky na studenta

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

· Umělá inteligence jako vědní disciplína, jazyky umělé inteligence. Základní rysy PROLOGu. · Hledání řešení – klasické úlohy, grafy a stromy řešení. Prohledávání do hloubky a do šířky, heuristické prohledávání. · Expertní systémy, vývoj, charakteristické rysy, vlastnosti. Struktura expertního systému.Typy expertních úloh. Některé známé systémy. · Reprezentace znalostí – sémantické sítě, rámce, inferenční sítě. Pravidla a inferenční sítě – pravděpodobnostní přístup, fuzzy logika. Řídící mechanismy. · Lingvistická proměnná, vícehodnotová logika a lingvistické modely. · Neuronové sítě, jejich specifické rysy. Model neuronu. Základní aplikační oblasti neuronových sítí. Perceptron, jeho adaptace. · Vícevrstvé sítě a metoda backpropagation. Spojitý perceptron s intervalovým stavem excitace a zobecněná metoda backpropagation. · Rekurentní vícevrstvé neuronové sítě. · Kompetice, Kohonenovy mapy, samoorganizace. · Kohonenova síť s učitelem, Counter-Propagation. · Hopfieldova síť, identifikace předloženého vzoru. · Boltzmannův stroj, dvousměrná asociativní paměť. Adaptivní rezonanční teorie. · Expertní systémy využívající neuronové sítě. Neuronové zpracování obrazové informace.

Conditions for subject completion

Combined form (validity from: 1960/1961 Summer semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Exercises evaluation and Examination Credit and Examination 100 (100) 51
        Exercises evaluation Credit 33 (33) 0
                Project Project 20  0
                Written exam Written test 10  0
                Other task type Other task type 3  0
        Examination Examination 67 (67) 0
                Written examination Written examination 50  0
                Oral Oral examination 17  0
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2005/2006 (N3646) Geodesy and Cartography (3602T002) Geoinformatics (10) K Czech Ostrava 1 Compulsory study plan
2004/2005 (N3646) Geodesy and Cartography (3602T002) Geoinformatics (10) K Czech Ostrava 1 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner