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Wyszukujesz frazę "fuzzy decision trees" wg kryterium: Temat


Wyświetlanie 1-3 z 3
Tytuł:
Machine fault diagnosis and condition prognosis using classification and regression trees and neuro-fuzzy inference systems
Autorzy:
Tran, V. T.
Yang, B. S.
Powiązania:
https://bibliotekanauki.pl/articles/971018.pdf
Data publikacji:
2010
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
fault diagnosis
classification
induction motors
decision trees
forecasts
fuzzy systems
Opis:
This paper presents an approach to machine fault diagnosis and condition prognosis based on classification and regression trees (CART) and neuro-fuzzy inference systems (ANFIS). In case of diagnosis, CART is used as a feature selection tool to select pertinent features from data set, while ANFIS is used as a classifier. The crisp rules obtained from CART are then converted to fuzzy if-then rules, employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. The data sets obtained from vibration signals and current signals of the induction motors are used to evaluate the proposed algorithm. In case of prognosis, both of these models in association with direct prediction strategy for long-term prediction of time series techniques are utilized to forecast the future values of machine operating condition. In this case, the number of available observations and the number of predicted steps are initially determined by false nearest neighbor method and auto mutual information technique, respectively. These values are subsequently utilized as inputs for prediction models. The performance of the proposed prognosis system is then evaluated by using real trending data of a low methane compressor. A comparative study of the predicted results obtained from CART and ANFIS models is also carried out to appraise the prediction capability of these models. The results of the proposed methods in both cases indicate that CART and ANFIS offer a potential for machine fault diagnosis and for condition prognosis.
Źródło:
Control and Cybernetics; 2010, 39, 1; 25-55
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Handwrittenword recognition using fuzzy matching degrees
Autorzy:
Wróbel, Michał
Starczewski, Janusz T.
Fijałkowska, Justyna
Siwocha, Agnieszka
Napoli, Christian
Powiązania:
https://bibliotekanauki.pl/articles/2031113.pdf
Data publikacji:
2021
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
offline handwriting recognition
handwritten strokes
fuzzy matching degrees
interval type-2 fuzzy sets
decision trees
bigram frequency
Opis:
Handwritten text recognition systems interpret the scanned script images as text composed of letters. In this paper, efficient offline methods using fuzzy degrees, as well as interval fuzzy degrees of type-2, are proposed to recognize letters beforehand decomposed into strokes. For such strokes, the first stage methods are used to create a set of hypotheses as to whether a group of strokes matches letter or digit patterns. Subsequently, the second-stage methods are employed to select the most promising set of hypotheses with the use of fuzzy degrees. In a primary version of the second-stage system, standard fuzzy memberships are used to measure compatibility between strokes and character patterns. As an extension of the system thus created, interval type-2 fuzzy degrees are employed to perform a selection of hypotheses that fit multiple handwriting typefaces.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 3; 229-242
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Patient classification algorithm at urgency care area of a hospital based on the triage system
Autorzy:
Mondragon, N.
Istrate, D.
Wegrzyn-Wolska, K.
Garcia, J. C.
Sanchez, J.C.
Powiązania:
https://bibliotekanauki.pl/articles/951692.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
triage
classification
SET
fuzzy logic
decision trees
patients
urgency
hospital emergency
algorithm
ocena stanu zdrowia rannych
klasyfikacja
logika rozmyta
drzewa decyzyjne
pacjenci
pomoc szpitalna
algorytm
Opis:
The time passed in the urgency zone of a hospital is really important, and the quick evaluation and selection of the patients who arrive to this area is essential to avoid waste of time and help the patients in a higher emergency level. The triage, an evaluation and classification structured system, allows to manage the urgency level of the patient; it is based on the vital signs measures and clinical data of the patient. The goal is making the classification in the shortest possible time and with a minimal error percentage. Levels are allocated according to the concept that what is urgent is not always serious and that what is serious is not always urgent. In this work, we present a computational algorithm that evaluates the patients within the fever symptomatic category, we use fuzzy logic and decision trees to collect and analyze simultaneously the vital signs and the clinical data of the patient through a graphical interface; so that the classification can be more intuitive and faster. Fuzzy logic allows us to process data and take a decision based on incomplete information or uncertain values, decision trees are structures or rules sets that classify the data when we have several variables.
Źródło:
Journal of Medical Informatics & Technologies; 2013, 22; 87-94
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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