Výsledky vyhledávání - "Alzubi, Maen"

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Fuzzy Rule Interpolation Toolbox for the GNU Open-Source OCTAVE

Autor: Alzubi, Maen, Almseidin, Mohammad, Lone, Mohd Aaqib, Kovacs, Szilveszter

In most fuzzy control applications (applying classical fuzzy reasoning), the reasoning method requires a complete fuzzy rule-base, i.e all the possible observations must be covered by the antecedents of the fuzzy rules, which is not always available.

Externí odkaz: http://arxiv.org/abs/1912.04999

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Some Considerations and a Benchmark Related to the CNF Property of the Koczy-Hirota Fuzzy Rule Interpolation

Autor: Alzubi, Maen, Kovacs, Szilveszter

Publikováno v: International Journal on Advanced Science, Engineering and Information Technology 2019. Vol.9. No 5

The goal of this paper is twofold. Once to highlight some basic problematic properties of the KH Fuzzy Rule Interpolation through examples, secondly to set up a brief Benchmark set of Examples, which is suitable for testing other Fuzzy Rule Interpola

Externí odkaz: http://arxiv.org/abs/1911.05041

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Investigating The Piece-Wise Linearity And Benchmark Related To Koczy-Hirota Fuzzy Linear Interpolation

Autor: Alzubi, Maen, Kovács, Szilvester

Publikováno v: Journal of Theoretical and Applied Information Technology 15th June 2019. Vol.97. No 11

Fuzzy Rule Interpolation (FRI) reasoning methods have been introduced to address sparse fuzzy rule bases and reduce complexity. The first FRI method was the Koczy and Hirota (KH) proposed "Linear Interpolation". Besides, several conditions and criter

Externí odkaz: http://arxiv.org/abs/1907.01047

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Fuzzy Rule Interpolation Methods and Fri Toolbox

Autor: Alzubi, Maen, Johanyák, Zsolt Csaba, Kovács, Szilveszter

Publikováno v: Journal of Theoretical and Applied Information Technology 15th November 2018. Vol.96. No 21

FRI methods are less popular in the practical application domain. One possible reason is the missing common framework. There are many FRI methods developed independently, having different interpolation concepts and features. One trial for setting up

Externí odkaz: http://arxiv.org/abs/1904.12178

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Evaluation of Machine Learning Algorithms for Intrusion Detection System

Autor: Almseidin, Mohammad, Alzubi, Maen, Kovacs, Szilveszter, Alkasassbeh, Mouhammd

Publikováno v: Intelligent Systems and Informatics (SISY), 2017 IEEE 15th International Symposium

Intrusion detection system (IDS) is one of the implemented solutions against harmful attacks. Furthermore, attackers always keep changing their tools and techniques. However, implementing an accepted IDS system is also a challenging task. In this pap

Externí odkaz: http://arxiv.org/abs/1801.02330

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