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Publikační činnost


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Typ záznamu * : stať ve sborníku (D)
Domácí pracoviště * : Katedra informatiky a počítačů (31400)
Název * : Use of neural networks for adaptive e-learning: A preliminary study
Citace : Bradáč, V., Jarušek, R., Volná, E. a Kotyrba, M. Use of neural networks for adaptive e-learning: A preliminary study. In: 16th European Conference on e-Learning, ECEL 2017: Proceedings of the European Conference on e-Learning, ECEL 2017-10-27 Porto; Portugal. UK: Academic Conferences Limited, 2017. s. 78-84. ISBN 978-191121859-3.
Podnázev :
Rok * : 2017
Obor * : Informatika
Počet stran * : 7
Strana od * : 78
Strana do * : 84
Forma vydání * : Tištená verze
Kód ISBN * : 978-191121859-3
Kód ISSN : 2048-8637
Název sborníku * : Proceedings of the European Conference on e-Learning, ECEL
Sborník : Mezinárodní
Název nakladatele * : Academic Conferences Limited
Místo vydání * : UK
Stát vydání : Sborník vydaný v zahraničí
Název konference : 16th European Conference on e-Learning, ECEL 2017
Místo konání konference * : Porto; Portugal
Datum zahájení konference * :
Typ akce podle státní
příslušnosti účastníků akce * :
Celosvětová akce
Kód UT WoS : 000457842600011
EID : 2-s2.0-85037540179
Klíčová slova anglicky * :
Adaptive systems; Computation theory; E-learning; Education; Electronic trading; Expert systems; Fuzzy inference; Fuzzy neural networks; Knowledge based systems; Neural networks; Adaptive characteristic; Adaptive e-learning; Adaptivity; Fuzzy expert systems; Knowledge base; Neural computing; Scientific discipline; Testing phase; Fuzzy logic
Popis v původním jazyce * :
Neural Computing, e.g. Artificial Neural Networks, is one of the most interesting and rapidly growing areas of research, attracting researchers from a wide variety of scientific disciplines. Starting from the basics, Neural Computing covers all the major approaches, putting each in perspective in terms of their capabilities, advantages, and disadvantages. Their use primarily focuses on predicting future behaviour of the given area, e.g. stock market. Adaptive system is able to react to changes from the outside aiming at minimizing the deviation from the required values that characterise the required state or behaviour of the system. Current adaptive systems take advantage of the use of expert systems. Unlike expert systems that use a predefined knowledge base of rules, neural networks learn from a set of examples thus creating their own unique configuration. The aim of this paper is to consider the use of neural networks in an existing e-learning system featuring adaptive characteristics based on a fuzzy expert system. Neural networks are used as a classifier, which generates personal study plans of students and are able to replace the previously used expert system. Nowadays, the experimental study of the whole proposed classifier is in a testing phase. Neural networks should then replace the fuzzy expert system with the goal to outperform it and to provide more accurate and suitable outputs. The final structure of the system should be simplified as the tool in the form of a series of neural networks. The proposed system should act as the only mediator between the tutor and the student in the process of creating a personalised study plan.
Popis v anglickém jazyce * :
Typ zdroje financování výsledku * : Specifický výzkum
Seznam projektů :
ID Projektu Název projektu
Seznam ohlasů : 
Ohlas
R01: RIV/61988987:17310/17:A1801QY3

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