Wszystkie pola: type-2 fuzzy logic system - Katalog OPAC zbiorów

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Tytuł:: An Architecture for Making Judgments Using Computing With Words
Autorzy:: Mendel, J. M.
Powiązania:: https://bibliotekanauki.pl/articles/908008.pdf
Data publikacji:: 2002
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: informatyka
computing with words
footprint of uncertainty
perceptual computer
type-2 fuzzy logic system
judgments
Opis:: Our thesis is that computing with words needs to account for the uncertainties associated with the meanings of words, and that these uncertainties require using type-2 fuzzy sets. Doing this leads to a proposed architecture for making judgments by means of computing with words, i.e., to a perceptual computer - the Per-C. The Per-C includes an encoder, a type-2 rule-based fuzzy logic system, and a decoder. It lets all human-computer interactions be performed using words. In this paper, a quantitative language is established for the Per-C, and many open issues about the perceptual computer are described.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2002, 12, 3; 325-335
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:: Users-centric adaptive learning system based on interval type-2 fuzzy logic for massively crowded e-learning platforms
Autorzy:: Almohammadi, K.
Hagras, H.
Alghazzawi, D.
Aldabbagh, G.
Powiązania:: https://bibliotekanauki.pl/articles/91622.pdf
Data publikacji:: 2016
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: Type-2 Fuzzy Logic systems
e-learning
intelligent learning environments
Opis:: Technological advancements within the educational sector and online learning promoted portable data-based adaptive techniques to influence the developments within transformative learning and enhancing the learning experience. However, many common adaptive educational systems tend to focus on adopting learning content that revolves around pre-black box learner modelling and teaching models that depend on the ideas of a few experts. Such views might be characterized by various sources of uncertainty about the learner response evaluation with adaptive educational system, linked to learner reception of instruction. High linguistic uncertainty levels in e-learning settings result in different user interpretations and responses to the same techniques, words, or terms according to their plans, cognition, pre-knowledge, and motivation levels. Hence, adaptive teaching models must be targeted to individual learners’ needs. Thus, developing a teaching model based on the knowledge of how learners interact with the learning environment in readable and interpretable white box models is critical in the guidance of the adaptation approach for learners’ needs as well as understanding the way learning is achieved. This paper presents a novel interval type-2 fuzzy logic-based system which is capable of identifying learners’ preferred learning strategies and knowledge delivery needs that revolves around characteristics of learners and the existing knowledge level in generating an adaptive learning environment. We have conducted a large scale evaluation of the proposed system via real-word experiments on 1458 students within a massively crowded e-learning platform. Such evaluations have shown the proposed interval type-2 fuzzy logic system’s capability of handling the encountered uncertainties which enabled to achieve superior performance with regard to better completion and success rates as well as enhanced learning compared to the non-adaptive systems, adaptive system versions led by the teacher, and type-1-based fuzzy based counterparts.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2016, 6, 2; 81-101
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: A robust fault diagnosis and forecasting approach based on Kalman filter and interval type-2 fuzzy logic for efficiency improvement of centrifugal gas compressor system
Autorzy:: Nail, Bachir
Kouzou, Abdellah
Hafaifa, Ahmed
Hadroug, Nadji
Puig, Vicenç
Powiązania:: https://bibliotekanauki.pl/articles/329190.pdf
Data publikacji:: 2019
Wydawca:: Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:: fault detection
diagnosis
centrifugal gas compressor
Kalman filter
interval type-2 fuzzy logic
experimental data
ARIMA
detekcja uszkodzeń
diagnostyka
filtr Kalmana
Opis:: The paper proposes a robust faults detection and forecasting approach for a centrifugal gas compressor system, the mechanism of this approach used the Kalman filter to estimate and filtering the unmeasured states of the studied system based on signals data of the inputs and the outputs that have been collected experimentally on site. The intelligent faults detection expert system is designed based on the interval type-2 fuzzy logic. The present work is achieved by an important task which is the prediction of the remaining time of the system under study to reach the danger and/or the failure stage based on the Auto-regressive Integrated Moving Average (ARIMA) model, where the objective within the industrial application is to set the maintenance schedules in precisely time. The obtained results prove the performance of the proposed faults diagnosis and detection approach which can be used in several heavy industrial systems.
Źródło:: Diagnostyka; 2019, 20, 2; 57-75
1641-6414
2449-5220
Pojawia się w:: Diagnostyka
Dostawca treści:: Biblioteka Nauki

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