Wszystkie pola: fuzzy methods - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Recent soft computing methods in software reliability engineering
Autorzy:: Albeanu, G.
Duda, G.
Powiązania:: https://bibliotekanauki.pl/articles/2069529.pdf
Data publikacji:: 2011
Wydawca:: Uniwersytet Morski w Gdyni. Polskie Towarzystwo Bezpieczeństwa i Niezawodności
Tematy:: fuzzy sets
intuitionistic fuzzy sets
intuitionistic fuzzy numbers
subjective data analysis
Opis:: This paper presents recent approaches in soft computing to manage imprecision and uncertainty which appear in software reliability engineering. Firstly, recent approaches like imprecise probabilities, generalized intervals, fuzzy sets and intuitionistic-fuzzy sets are shortly described, and the usage of intuitionistic fuzzy numbers for system reliability computation is shown. Intuitionistic-fuzzy approaches for software reliability growth models are proposed and experimental results are given.
Źródło:: Journal of Polish Safety and Reliability Association; 2011, 2, 1; 1--10
2084-5316
Pojawia się w:: Journal of Polish Safety and Reliability Association
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Combining fuzzy and cellular learning automata methods for clustering wireless sensor network to increase life of the network
Autorzy:: Aramideh, J
Jelodar, H
Powiązania:: https://bibliotekanauki.pl/articles/957968.pdf
Data publikacji:: 2014
Wydawca:: Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:: wireless sensor network
clustering
fuzzy logic
cellular learning automata
Opis:: Wireless sensor networks have attracted attention of researchers considering their abundant applications. One of the important issues in this network is limitation of energy consumption which is directly related to life of the network. One of the main works which have been done recently to confront with this problem is clustering. In this paper, an attempt has been made to present clustering method which performs clustering in two stages. In the first stage, it specifies candidate nodes for being head cluster with fuzzy method and in the next stage, the node of the head cluster is determined among the candidate nodes with cellular learning automata. Advantage of the clustering method is that clustering has been done based on three main parameters of the number of neighbors, energy level of nodes and distance between each node and sink node which results in selection of the best nodes as a candidate head of cluster nodes. Connectivity of network is also evaluated in the second part of head cluster determination. Therefore, more energy will be stored by determining suitable head clusters and creating balanced clusters in the network and consequently, life of the network increases.
Źródło:: Advances in Science and Technology. Research Journal; 2014, 8, 24; 1-8
2299-8624
Pojawia się w:: Advances in Science and Technology. Research Journal
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Using artificial immune and case-based reasoning methods in classification of treatment effectiveness
Autorzy:: Badura, D.
Ferdynus, D.
Powiązania:: https://bibliotekanauki.pl/articles/333874.pdf
Data publikacji:: 2007
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: wnioskowanie bazujące na przykładach
sztuczne systemy immunologiczne
sieci neuronowe rozmyte
case-based reasoning
artificial immune system
fuzzy neural nets
Opis:: The article concerns the analysis of classification of medical data by use of selected method of artificial intelligence: case-based reasoning. The subject of the research is the assessment of effective treatment, being one of the most important medical problems. The basis work of the assessment system should be one of the classification methods. The aim of the attempted research is to study which of the enumerated method will be able to group data containing incomplete information in the best way. The classified data are descended from the patients with nephroblastoma and patients with backbone pain. The final aim of the research is to work out the functioning method of the learning system, assisting the doctor with making a decision during working out on patient's treatment therapy, and making analyses of the treatment effectiveness. On the basis of the medical tests, the system will classify the data assigning them to the appropriate therapy groups. Moreover, in the system will be used artificial immunology as the method of generalizing or extrapolating of the gathering and considering so far cases.
Źródło:: Journal of Medical Informatics & Technologies; 2007, 11; 221-226
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Sensitivity analysis of fuzzy-analytic hierarchical process (FAHP) decision-making model in selection of underground metal mining method
Autorzy:: Balusa, Bhanu Chander
Gorai, Amit Kumar
Powiązania:: https://bibliotekanauki.pl/articles/91925.pdf
Data publikacji:: 2019
Wydawca:: Główny Instytut Górnictwa
Tematy:: decision-making
mining methods
fuzzy AHP
sensitivity analysis
podejmowanie decyzji
metody wydobycia
rozmyty analityczny proces hierarchiczny
analiza wrażliwości
Opis:: This study aims to analyse the sensitivity in decision-making which results in the selection of the appropriate underground metal mining method using the fuzzy-analytical hierarchy process (FAHP) model. The proposed model considers sixteen criteria for the selection of the most appropriate mining method out of the seven. The model consists of three-layer viz. the first layer represents the criteria (factors which influence the mining method), the second layer represents the sub-criteria (categorisation of the factors) and the third layer represents the alternatives (mining methods). The priority of the different mining methods was determined based on global weights. The global weights of seven mining method were determined using a different fuzzification factor under different decision-making attitudes (optimistic, pessimistic and unbiased). The sensitivity of the decision-making results was analysed in order to understand the robustness of the model.
Źródło:: Journal of Sustainable Mining; 2019, 18, 1; 8-17
2300-1364
2300-3960
Pojawia się w:: Journal of Sustainable Mining
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Pomiędzy TAK a NIE czyli o rozmytym charakterze pojęć, metod i kategorii
Between the yes and the no – on fuzzy character of concepts, methods and categories
Autorzy:: Bogocz, Danuta
Powiązania:: https://bibliotekanauki.pl/articles/452989.pdf
Data publikacji:: 2012
Wydawca:: Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Katedra Ekonometrii i Statystyki
Tematy:: zbiór rozmyty
ubóstwo
ranking
fuzzy sets
poverty
Opis:: W pracy przedstawiono garść rozważań nad rozmytym podejściem do analizy niektórych zjawisk, wynikającym z nieostrych granic definiujących dotyczące ich pojęcia. W celu lepszego zobrazowania rozmytego charakteru stosowanych procedur oraz ich wyników wykorzystano przykład empiryczny.
The paper presents an investigation within the subject of fuzzy methodology concerning some phenomena, which is the consequence of their fuzzy nature. In order to illustrate some fuzzy procedures and their results an empirical example is included.
Źródło:: Metody Ilościowe w Badaniach Ekonomicznych; 2012, 13, 1; 49-57
2082-792X
Pojawia się w:: Metody Ilościowe w Badaniach Ekonomicznych
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Solution of Material Selection Problem Using Fuzzy Axiomatic Design and DEMATEL Methods
Autorzy:: Candan, G.
Kir, S.
Yazgan, H.
Powiązania:: https://bibliotekanauki.pl/articles/1030368.pdf
Data publikacji:: 2017-01
Wydawca:: Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:: 89.20.Kk
89.65.Gh
Opis:: Material selection is an important task for dental healthcare. A teeth can be filled with several filling materials such as a silver amalgam (mixed with silver, tin, zinc, and copper), a plastic, a porcelain, and composites. Choosing the best filling material is a complex process for a dentist because of human healthcare. There are many criteria for the selection process such as aesthetics, resistant, strength, rigid, long life, low cost, healthy. One of the novelty of this research that is the first research in the field of selecting dental material and another novelty that is used fuzzy axiomatic design and fuzzy DEMATEL methods together first time. First of all, the most effective criteria are determined in order to choose the best material. The weights of the criteria are determined using interaction among themselves. Interactions among criteria are found using DEMATEL method with taking into consideration of dentists' experiences on a teeth filling. Secondly, evaluating alternative materials is carried out using fuzzy axiomatic design method. The results illustrate that the proposed approach is suitable for selecting materials of a teeth filling. We believe that the approach can be applicable for other material selection problems.
Źródło:: Acta Physica Polonica A; 2017, 131, 1; 24-27
0587-4246
1898-794X
Pojawia się w:: Acta Physica Polonica A
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Accumulation methods in the processing of difficult images
Autorzy:: Chmielewski, L.J.
Powiązania:: https://bibliotekanauki.pl/articles/332880.pdf
Data publikacji:: 2008
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: analiza obrazu
gromadzenie dowodów
metody rozmyte
histogram
transformata Hough'a
image analysis
evidence accumulation
fuzzy methods
Hough transform
Opis:: The accumulation methods emerged in close relation to the development of the Hough transform (HT). The application of some far reaching generalizations of the HT will be presented. The accumulation principle will be taken as a starting point: Accumulate the relevant data from possibly many, possibly competent sources. This principle is known and widely used in image processing, mainly in the methods related to the HT. The principle is in opposition to the tendency to compress the image data as early in the processing as possible. The accumulation principle is a recommendation to utilize the redundancy in the image data in a specific way and should be applied when the images are difficult to process due to their low quality. The basic data structure is the fuzzy histogram, which is in fact an experimentally obtained approximation of the probability density of the phenomenon of interest. The concepts of a degree of fuzzification and the weakly and strongly fuzzified histograms will be introduced. A number of solutions found with the use of the accumulation principle will be presented. In the examples and tests, biomedical images will be used. Such images are challenging because the objects imaged are irregular and the quality of the images is usually limited in a natural way by the imaging modalities used. The accumulation methods are a good solution to the problem of analysis of such images.
Źródło:: Journal of Medical Informatics & Technologies; 2008, 12; 11-21
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: New Methods for Designing and Reduction of Neuro-Fuzzy Systems
Autorzy:: Cpałka, K.
Powiązania:: https://bibliotekanauki.pl/articles/108790.pdf
Data publikacji:: 2010
Wydawca:: Społeczna Akademia Nauk w Łodzi
Tematy:: algorithm of best global eliminations
algorithm of best local eliminations
consecutive eliminations algorithm
consecutive mergings algorithm
interpretability
logical approach
neuro-fuzzy system
Opis:: In the paper, we propose novel methods for designing and reduction of neuro-fuzzy systems without the deterioration of their accuracy. The reduction and merging algorithms gradually eliminate inputs, rules, antecedents, and the number of discretization points of integrals in the center of area defuzzification method. Our algorithms have been tested using well known classification benchmark.
Źródło:: Journal of Applied Computer Science Methods; 2010, 2 No. 2; 113-126
1689-9636
Pojawia się w:: Journal of Applied Computer Science Methods
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Fuzzy clustering based methods for nystagmus movements detection in electronystagmography signal
Autorzy:: Czabański, R.
Pander, T.
Horoba, K.
Przybyła, T.
Powiązania:: https://bibliotekanauki.pl/articles/332952.pdf
Data publikacji:: 2013
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: saccade detection
optokinetic nystagmus
fuzzy clustering
detekcja ruchów sakadowych
oczopląs optokinetyczny
grupowanie rozmyte
sygnał ENG
Opis:: The analysis of optokinetic nystagmus (OKN) provides valuable information about the condition of human vision system. One of the phenomena that is used in the medical diagnosis is optokinetic nystagmus. Nystagmus are voluntary or involuntarily eye movements being a response to a stimuli which activate the optokinetic systems. The electronystagmography (ENG) signal corresponding to the nystagmus has a form of a saw tooth waveform with fast components related to saccades. The accurate detection of the saccades in the ENG signal is the base for the further estimation of the nystagmus characteristic. The proposed algorithm is based on the proper filtering of the ENG signal providing a waveform with amplitude peaks corresponding the fast eyes rotation. The correct recognition of the local maxima of the signal is obtained by the means of fuzzy c-means clustering (FCM). The paper presents three variants of saccades detection algorithm based on the FCM. The performance of the procedures was investigated using the artificial as well as the real optokinetic nystagmus cycles. The proposed method provides high detection sensitivity and allows for the automatic and precise determination of the saccades location in the preprocessed ENG signal.
Źródło:: Journal of Medical Informatics & Technologies; 2013, 22; 277-283
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

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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Skocz do pozycji: 11.

Tytuł:: Klasyfikator lokalnych uszkodzeń zębów kół przekładni, wykorzystujący logikę rozmytą oraz selekcję widmową
Classifier of fault diagnosis in a gear wheel which used fuzzy logic and fast Fourier transform
Autorzy:: Czech, P.
Powiązania:: https://bibliotekanauki.pl/articles/256160.pdf
Data publikacji:: 2008
Wydawca:: Sieć Badawcza Łukasiewicz - Instytut Technologii Eksploatacji - Państwowy Instytut Badawczy
Tematy:: diagnostyka
przekładna zębata
metoda sztucznej inteligencji
logika rozmyta
diagnostics
toothed gears
artificial intelligent methods
fuzzy logic
Opis:: W artykule przedstawiono wyniki prób mających na celu budowę klasyfikatora lokalnych uszkodzeń zębów kół przekładni, zbudowanego w oparciu o logikę rozmytą. Obiekt badań stanowiła przekładnia zębata o zębach prostych, pracująca na stanowisku mocy krążącej FZG. Badaniami objęto przekładnie z kołami bez uszkodzeń oraz z lokalnymi uszkodzeniami zębów w postaci pęknięcia u podstawy zęba i wykruszenia wierzchołka zęba. W artykule zaproponowano sposób budowy systemów diagnozujących lokalne uszkodzenia zębów kół. Do tego celu wykorzystano sygnały drganiowe poddane odpowiedniej filtracji oraz przetwarzaniu.
The present paper presents the results of an experimental application of a fuzzy logic system as a classifier of the degree of cracking root and chipping tip of the tooth in a gear wheel. The input data for the classifier was in the form of a matrix composed of statistical measures, obtained from fast Fourier transform analysis. In order to create a foundation for knowledge, a stand testing was done. The experimental tests were conducted in the system operating as circulating power test rigs. As the result, the method of standard construction for diagnostic systems based on fuzzy logic was also worked out by means of defining the ways of filtrating and analysing of signals. Additionally, the procedure of building the fuzzy logic system used to classify the state of an object was researched.
Źródło:: Problemy Eksploatacji; 2008, 1; 55-73
1232-9312
Pojawia się w:: Problemy Eksploatacji
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 12.

Tytuł:: Registration and fuzzy segmentation modules for SemiVis framework
Autorzy:: Denkowski, M.
Chlebiej, M.
Mikołajczak, P.
Powiązania:: https://bibliotekanauki.pl/articles/333861.pdf
Data publikacji:: 2005
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: struktura przetwarzania obrazów
rejestracja
rozmyta metoda segmentacji
wizualizacja
przetwarzanie obrazu rezonansu magnetycznego mózgu
image processing framework
registration
fuzzy segmentation methods
visualization
MR brain image processing
Opis:: This paper presents the cross-platform framework for image processing with a focus on medical imaging. It allows a fast addition and testing of new algorithms using a modular structure. New modules can be created by using a platform-independent The C++ class library can be easily integrated with a whole system by a plug-in mechanisms. Together with the system core in the framework medical image processing modules are included. The plug-in mechanism allows to create a processing pipelines of this modules to achieve sophisticated processing functions such as registration or segmentation.
Źródło:: Journal of Medical Informatics & Technologies; 2005, 9; 65-74
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 13.

Tytuł:: Segmentation and visualisation MR images of the human brain
Autorzy:: Denkowski, M.
Chlebiej, M.
Mikołajczak, P.
Powiązania:: https://bibliotekanauki.pl/articles/333556.pdf
Data publikacji:: 2004
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: metody segmentacji
wizualizacja
przetwarzanie obrazu rezonansu magnetycznego mózgu
logika rozmyta
powierzchnia
interpretacja objętościowa
segmentation methods
visualization
MR brain image processing
thresholding
fuzzy logic
surface
volumetric rendering
Opis:: Segmentation and visualisation of anatomical regions of the brain are fundamental problems in medical image analysis. In this paper, we present a fuzzy-logic segmentation system that is capable of segmenting magnetic resonance (MR) images of a human brain. The presented method consists of two main stages: histogram thresholding and pixel classification using a rule-based fuzzy logic inference. After the segmentation is complete, attributes of different tissue classes may be determined (e.g., volumes), or the classes may be visualised as spatial objects. The implemented system provides many advanced 3D imaging tools.
Źródło:: Journal of Medical Informatics & Technologies; 2004, 7; MIP59-68
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 14.

Tytuł:: Neural methods of knowledge extraction
Autorzy:: Duch, W.
Adamczak, R.
Grąbczewski, K.
Jankowski, N.
Powiązania:: https://bibliotekanauki.pl/articles/206250.pdf
Data publikacji:: 2000
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:: diagnostyka medyczna
optymalizacja
reguła logiczna
reguła rozmyta
wspomaganie decyzji
data mining
decision support
fuzzy rules
logical rules
medical diagnosis
optimization
Opis:: Contrary to the common opinion, neural networks may be used for knowledge extraction. Recently, a new methodology of logical rule extraction, optimization and application of rule-based systems has been described. C-MLP2LN algorithm, based on constrained multilayer perceptron network, is described here in details and the dynamics of a transition from neural to logical system illustrated. The algorithm handles real-valued features, determining appropriate linguistic variables or membership functions as a part of the rule extraction process. Initial rules are optimized by exploring the accuracy/simplicity tradeoff at the rule extraction stage and the one between reliability of rules and rejection rate at the optimization stage. Gaussian uncertainties of measurements are assumed during application of crisp logical rules, leading to "soft trapezoidal" membership functions and allowing to optimize the linguistic variables using gradient procedures. Comments are made on application of neural networks to knowledge discovery in the benchmark and real life problems.
Źródło:: Control and Cybernetics; 2000, 29, 4; 997-1017
0324-8569
Pojawia się w:: Control and Cybernetics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 15.

Tytuł:: A new auto adaptive fuzzy hybrid particle swarm optimization and genetic algorithm
Autorzy:: Dziwiński, Piotr
Bartczuk, Łukasz
Paszkowski, Józef
Powiązania:: https://bibliotekanauki.pl/articles/1837533.pdf
Data publikacji:: 2020
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: hybrid methods
Particle Swarm Optimization
Genetic Algorithm
fuzzy systems
multimodal function
Opis:: The social learning mechanism used in the Particle Swarm Optimization algorithm allows this method to converge quickly. However, it can lead to catching the swarm in the local optimum. The solution to this issue may be the use of genetic operators whose random nature allows them to leave this point. The degree of use of these operators can be controlled using a neuro-fuzzy system. Previous studies have shown that the form of fuzzy rules should be adapted to the fitness landscape of the problem. This may suggest that in the case of complex optimization problems, the use of different systems at different stages of the algorithm will allow to achieve better results. In this paper, we introduce an auto adaptation mechanism that allows to change the form of fuzzy rules when solving the optimization problem. The proposed mechanism has been tested on benchmark functions widely adapted in the literature. The results verify the effectiveness and efficiency of this solution.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 2; 95-111
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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