Temat: implikacja rozmyta - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Implication-Based Neuro-Fuzzy Architectures
Autorzy:: Rutkowska, D.
Nowicki, R.
Powiązania:: https://bibliotekanauki.pl/articles/911144.pdf
Data publikacji:: 2000
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: system rozmyty
implikacja rozmyta
wnioskowanie rozmyte
neuro-fuzzy systems
fuzzy implications
fuzzy inference
Mamdani approach
logical approach
connectionist architectures
Opis:: This paper presents connectionist multi-layer architectures of neuro-fuzzy systems based on various fuzzy implications. The well-known Mamdani approach (constructive) and the logical approach (destructive) are considered. Two kinds of architectures, a simpler and a more general one, are distinguished. Examples of application to classification and control problems are provided.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2000, 10, 4; 675-701
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Higher order fuzzy logic in controlling selective catalytic reduction systems
Autorzy:: Niewiadomski, A.
Kacprowicz, M.
Powiązania:: https://bibliotekanauki.pl/articles/201190.pdf
Data publikacji:: 2014
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: Selective Catalytic Reduction
SCR
air pollution
nitrogen oxides
adjustable air filter
ammonia valve
interval-valued fuzzy logic system
fuzzy controlling of air filter adjustments
type-2 fuzzy logic system
fuzzy implications
selektywna redukcja katalityczna SCR
zanieczyszczenia powietrza
tlenki azotu
regulowane filtry powietrza
zawór amoniaku
rozmyte kontrolowanie zmian filtra powietrza
typ-2 systemu logiki rozmytej
implikacja rozmyta
Opis:: This paper presents research on applications of fuzzy logic and higher-order fuzzy logic systems to control filters reducing air pollution [1]. The filters use Selective Catalytic Reduction (SCR) method and, as for now, this process is controlled manually by a human expert. The goal of the research is to control an SCR system responsible for emission of nitrogen oxide (NO) and nitrogen dioxide (NO2) to the air, using SCR with ammonia (NH3). There are two higher-order fuzzy logic systems presented, applying interval-valued fuzzy sets and type-2 fuzzy sets, respectively. Fuzzy sets and higher order fuzzy sets describe linguistically levels of nitrogen oxides as the input, and settings of ammonia valve in the air filter as the output. The obtained results are consistent with data provided by experts. Besides, we show that the type-2 fuzzy logic controllers allows us to obtain results much closer to desired parameters of the ammonia valve, than traditional FLS.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2014, 62, 4; 743-750
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: A Neuro-Fuzzy System Based on Logical Interpretation of If-then Rules
Autorzy:: Łęski, J.
Henzel, N.
Powiązania:: https://bibliotekanauki.pl/articles/911145.pdf
Data publikacji:: 2000
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: system rozmyty
implikacja rozmyta
fuzzy implications
approximate reasoning
neuro-fuzzy systems
soft computing
Opis:: Several important fuzzy implications and their properties are described on the basis of an axiomatic approach to the definition of the fuzzy implications. Then the idea of approximate reasoning using the generalized modus ponens and fuzzy implications is considered. The elimination of the non-informative part of the final fuzzy set before defuzzification plays the key role in this paper. After reviewing well-known fuzzy systems, a new artificial neural network based on logical interpretation of if-then rules (ANBLIR) is introduced. Moreover, this system automatically generates rules from numerical data. Applications of ANBLIR to pattern recognition on numerical examples using benchmark databases are indicated.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2000, 10, 4; 703-722
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Improving the quality of the fetal state assessment with epsilon-insensitive learning methods
Autorzy:: Czabański, R.
Wróbel, J.
Jeżewski, J.
Łęski, J.
Powiązania:: https://bibliotekanauki.pl/articles/333468.pdf
Data publikacji:: 2014
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: fetal monitoring
fuzzy implication
epsilon-insensitive learning
monitorowanie płodu
implikacja rozmyta
Opis:: Recording and analysis of fetal heart rate (FHR) signal is nowadays the primary method for the biophysical assessment of the fetal state. Since the correct interpretation of crucial FHR characteristics is difficult, methods of automated quantitative signal evaluation are still the subject of the research studies. In the following paper we investigated the possibility of improvement of the fetal state evaluation on the basis of the epsilon-insensitive learning (eIL). We examined two eIL procedures integrated with fuzzy clustering algorithms as well as different methods of logical interpretation of the fuzzy conditional statements. The quality of the FHR signal classification was evaluated using the data collected with the computerized fetal surveillance system. The learning performance was measured with the number of correct classification (CC) and overall quality index (QI) defined as a geometric mean of sensitivity and specificity. The obtained results (CC = 88 % and QI = 87 %) show a high efficiency of the fetal state assessment using the epsilon-insensitive learning based methods.
Źródło:: Journal of Medical Informatics & Technologies; 2014, 23; 19-26
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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