541-0545/01 – Expert Systems in GIS (ES_GIS)

Gurantor department	Department of Geological Engineering	Credits	4
Subject guarantor	Doc. PaedDr. Vladimír Homola, Ph.D.	Subject version guarantor	doc. RNDr. František Staněk, Ph.D.
Study level	undergraduate or graduate	Requirement	Compulsory
Year	4	Semester	summer
		Study language	Czech
Year of introduction	1997/1998	Year of cancellation	2009/2010
Intended for the faculties	HGF	Intended for study types	Master

Instruction secured by
Login	Name	Tuitor	Teacher giving lectures
STA22	doc. RNDr. František Staněk, Ph.D.

Extent of instruction for forms of study
Form of study	Way of compl.	Extent
Full-time	Credit and Examination	2+2
Part-time	Credit and Examination	15+15

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. 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., Brooks Cole, 2004

Recommended literature:

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

Way of continuous check of knowledge in the course of semester

E-learning

Other requirements

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. · Objektově orientovaný přístup k neuronovým sítím. · Expertní systémy využívající neuronové sítě. Neuronové zpracování obrazové informace.

Conditions for subject completion

Full-time form (validity from: 1960/1961 Summer semester)

Task name	Type of task	Max. number of points (act. for subtasks)	Min. number of points	Max. počet pokusů
Exercises evaluation and Examination	Credit and Examination	100 (100)	51	3
Exercises evaluation	Credit	33 (33)	0	3
Project	Project	20	0	3
Written exam	Written test	10	0	3
Other task type	Other task type	3	0	3
Examination	Examination	67 (67)	0	3
Written examination	Written examination	50	0	3
Oral	Oral examination	17	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 year	Programme	Branch/spec.	Spec.	Form	Study language	Tut. centre	Year	Type of duty
2005/2006	(M3646) Geodézie a kartografie	(3602T002) Geoinformatics		P	Czech	Ostrava	4	Compulsory	study plan
2005/2006	(N3646) Geodesy and Cartography	(3602T002) Geoinformatics	(10)	P	Czech	Ostrava	1	Compulsory	study plan
2004/2005	(M3646) Geodézie a kartografie	(3602T002) Geoinformatics		P	Czech	Ostrava	4	Compulsory	study plan
2004/2005	(N3646) Geodesy and Cartography	(3602T002) Geoinformatics	(10)	P	Czech	Ostrava	1	Compulsory	study plan
2003/2004	(M3646) Geodézie a kartografie	(3602T002) Geoinformatics		P	Czech	Ostrava	4	Compulsory	study plan
2003/2004	(N3646) Geodesy and Cartography	(3602T002) Geoinformatics	(10)	P	Czech	Ostrava	1	Compulsory	study plan
2002/2003	(M3646) Geodézie a kartografie	(3602T002) Geoinformatics		P	Czech	Ostrava	4	Compulsory	study plan
2001/2002	(M3646) Geodézie a kartografie	(3602T002) Geoinformatics		P	Czech	Ostrava	4	Compulsory	study plan
2000/2001	(M3646) Geodézie a kartografie	(3602T002) Geoinformatics		P	Czech	Ostrava	4	Compulsory	study plan

Occurrence in special blocks

Block name	Academic year	Form of study	Study language	Year	W	S	Type of block	Block owner

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