541-0545/04 – Expert Systems in GIS (ES_GIS)
Gurantor department | Department of Geological Engineering | Credits | 5 |
Subject guarantor | Doc. PaedDr. Vladimír Homola, Ph.D. | Subject version guarantor | Doc. PaedDr. Vladimír Homola, Ph.D. |
Study level | undergraduate or graduate | Requirement | Choice-compulsory |
Year | 1 | Semester | summer |
| | Study language | Czech |
Year of introduction | 1999/2000 | Year of cancellation | 2014/2015 |
Intended for the faculties | HGF | Intended for study types | Follow-up Master |
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
Písemné testy.
E-learning
Other requirements
Active participation in seminars and successful completion of written tests.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
Solving expert problems.
Fundamental principles of problem solving strategies.
Algorithmic implementation in PROLOG language.
Expert Systems.
Basic types of Artificial Neural Networks.
Conditions for subject completion
Conditions for completion are defined only for particular subject version and form of study
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.