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Tytuł:
New ranking method for fuzzy numbers by their expansion center
Autorzy:
Wang, Z.
Zhang-Westmant, L.
Powiązania:
https://bibliotekanauki.pl/articles/91710.pdf
Data publikacji:
2014
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
curve of the membership function
fuzzy number
horizontal real axis
expansion center
decision making
data analysis
fuzzy environment
geometric intuitivity
Opis:
Based on the area between the curve of the membership function of a fuzzy number and the horizontal real axis, a characteristic as a new numerical index, called the expansion center, for fuzzy numbers is proposed. An intuitive and reasonable ranking method for fuzzy numbers based on this characteristic is also established. The new ranking method is applicable for decision making and data analysis in fuzz environments. An important criterion of the goodness for ranking fuzzy numbers, the geometric intuitivity, is also introduced. It guarantees coinciding with the natural ordering of the real numbers.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2014, 4, 3; 181-187
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A fuzzy nonparametric Shewhart chart based on the bootstrap approach
Autorzy:
Wang, D.
Hryniewicz, O.
Powiązania:
https://bibliotekanauki.pl/articles/331218.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
Shewhart control chart
fuzzy data
bootstrap
average run length
karta kontrolna Shewharta
dane rozmyte
metoda bootstrap
Opis:
In this paper, we consider a nonparametric Shewhart chart for fuzzy data. We utilize the fuzzy data without transforming them into a real-valued scalar (a representative value). Usually fuzzy data (described by fuzzy random variables) do not have a distributional model available, and also the size of the fuzzy sample data is small. Based on the bootstrap methodology, we design a nonparametric Shewhart control chart in the space of fuzzy random variables equipped with some L2 metric, in which a novel approach for generating the control limits is proposed. The control limits are determined by the necessity index of strict dominance combined with the bootstrap quantile of the test statistic. An in-control bootstrap ARL of the proposed chart is also considered.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2015, 25, 2; 389-401
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Bitmap based structures for the modeling of fuzzy entities
Autorzy:
Verstraete, J.
Tre, G. de
Hallez, A.
Powiązania:
https://bibliotekanauki.pl/articles/970481.pdf
Data publikacji:
2006
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
imprecise GIS
uncertain GIS
fuzzy data modelling
fuzzy bitmaps
Opis:
Bitmap models are a known technique to model field based geographic information. Commonly, geographic information is modelled in a crisp sense, even though in reality it most likely is an approximation. In this article, we present the use of bitmap based structures to model imprecise or uncertain locations and ditto regions: these structures should be considered to be extensions of respectively a point and a polygon. The imprecission or uncertainty is modelled using fuzzy set theory. Apart from presenting the structures, appropriate operators are denned and explained.
Źródło:
Control and Cybernetics; 2006, 35, 1; 147-164
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Determination of system operation history based on oil field data
Genezowanie stanu technicznego systemu na podstawie badań właściwości oleju realizowanych w warunkach polowych
Autorzy:
Valis, D.
Zak, L.
Glos, J.
Walek, A.
Powiązania:
https://bibliotekanauki.pl/articles/347657.pdf
Data publikacji:
2012
Wydawca:
Akademia Wojsk Lądowych imienia generała Tadeusza Kościuszki
Tematy:
optymalizacja eksploatacji
trybodiagnostyka
dane eksploatacyjne
analiza regresji
dane rozmyte
maintenance optimization
tribo-diagnostics
field data
regression analysis
fuzzy logic
Opis:
The paper is to apply regression analysis methods with confidence intervals in order to analyse field data with the aim of finding the dependence of Fe particles occurrence on operating time. When comparing the results of the method/approach the authors believe that they can estimate the real operating profile of observed technical systems as well as its operating history. The results might be used for optimizing during an operation and maintenance phase.
W artykule wykorzystano metodę analizy regresji w określonych przedziałach ufności do badania systemów uzbrojenia eksploatowanych w warunkach polowych. Metoda ta posłużyła do przeanalizowania zależności występowania cząsteczek żelaza od czasu eksploatacji badanych systemów. Analiza porównawcza otrzymanych rezultatów wskazuje, że wykorzystana metoda daje możliwość oszacowania realnego trybu i czasu pracy badanych systemów. Otrzymane wyniki mogą być wykorzystanie do optymalizacji faz użytkowania i utrzymania rozpatrywanych systemów uzbrojenia.
Źródło:
Zeszyty Naukowe / Wyższa Szkoła Oficerska Wojsk Lądowych im. gen. T. Kościuszki; 2012, 4; 58-67
1731-8157
Pojawia się w:
Zeszyty Naukowe / Wyższa Szkoła Oficerska Wojsk Lądowych im. gen. T. Kościuszki
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Surrogate data: A novel approach to object detection
Autorzy:
Tabor, Z.
Powiązania:
https://bibliotekanauki.pl/articles/929568.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
dane zastępcze
ścieżka optymalna
powiązania rozmyte
surrogate data
optimal paths
fuzzy connectedness
Opis:
In the present study a novel method is introduced to detect meaningful regions of a gray-level noisy images of binary structures. The method consists in generating surrogate data for an analyzed image. A surrogate image has the same (or almost the same) power spectrum and histogram of gray-level values as the original one but is random otherwise. Then minmax paths are generated in the original image, each characterized by its length, minmax intensity and the intensity of the starting point. If the probability of the existence of a path with the same characteristics but within surrogate images is lower than some user-specified threshold, it is concluded that the path in the original image passes through a meaningful object. The performance of the method is tested on images corrupted by noise with varying intensity.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2010, 20, 3; 545-553
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy comprehensive model of manufacturing industry transfer risk based on economic big data analysis
Autorzy:
Sun, Tong
Liu, Chunzhi
Powiązania:
https://bibliotekanauki.pl/articles/2173644.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
economic big data
manufacturing industry
industrial transfer risk
entropy weight method
fuzzy model
duże zbiory danych ekonomicznych
przemysł wytwórczy
ryzyko transferu przemysłowego
metoda wag entropii
model rozmyty
Opis:
Aiming at the problems of low accuracy, low efficiency and low stability of traditional methods and recent developments in advanced technology incite the industries to be in sync with modern technology. With respect to various available techniques, this paper designs a fuzzy comprehensive evaluation model of the manufacturing industry for transferring risk based on economic big-data analytics. The big-data analysis method is utilized to obtain the data source of fuzzy evaluation of the manufacturing industry to transfer risk using data as the basis of risk evaluation. Based on the risk factors, the proposed model establishes the risk index system of the manufacturing industry and uses the expert evaluation method to design the scoring method of the evaluation index system. To ensure the accuracy of the evaluation results, the manufacturing industry’s fuzzy comprehensive model is established using the entropy weight method, and the expert evaluation results are modified accordingly. The experimental results show that the highest efficiency of the proposed method is 96%, the highest accuracy of the evaluation result is 75%. The evaluation result’s stability is higher than the other existing methods, which fully verifies the effectiveness and can provide a reliable theoretical basis for enterprise risk evaluation research.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 2; art. no. e139959
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
GrNFS: A granular neuro-fuzzy system for regression in large volume data
Autorzy:
Siminski, Krzysztof
Powiązania:
https://bibliotekanauki.pl/articles/2055169.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
granular computing
neuro-fuzzy system
large volume data
machine learning
przetwarzanie ziarniste
system neurorozmyty
uczenie maszynowe
Opis:
Neuro-fuzzy systems have proved their ability to elaborate intelligible nonlinear models for presented data. However, their bottleneck is the volume of data. They have to read all data in order to produce a model. We apply the granular approach and propose a granular neuro-fuzzy system for large volume data. In our method the data are read by parts and granulated. In the next stage the fuzzy model is produced not on data but on granules. In the paper we introduce a novel type of granules: a fuzzy rule. In our system granules are represented by both regular data items and fuzzy rules. Fuzzy rules are a kind of data summaries. The experiments show that the proposed granular neuro-fuzzy system can produce intelligible models even for large volume datasets. The system outperforms the sampling techniques for large volume datasets.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2021, 31, 3; 445--459
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparison of incomplete data handling techniques for neuro-fuzzy systems
Autorzy:
Sikora, M.
Simiński, K.
Powiązania:
https://bibliotekanauki.pl/articles/305722.pdf
Data publikacji:
2014
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
incomplete data
marginalization
imputation
neuro-fuzzy system
ANNBFIS
PDS
IFCM
OCS
NPS
Opis:
Real-life data sets sometimes miss some values. The incomplete data needs specialized algorithms or preprocessing that allows the use of the algorithms for complete data. The paper presents a comparison of various techniques for handling incomplete data in the neuro-fuzzy system ANNBFIS. The crucial procedure in the creation of a fuzzy model for the neuro-fuzzy system is the partition of the input domain. The most popular approach (also used in the ANNBFIS) is clustering. The analyzed approaches for clustering incomplete data are: preprocessing (marginalization and imputation) and specialized clustering algorithms (PDS, IFCM, OCS, NPS). The objective of our research is the comparison of the preprocessing techniques and specialized clustering algorithms to find the the most-advantageous technique for handling incomplete data with a neuro-fuzzy system. This approach is also the indirect validation of clustering.
Źródło:
Computer Science; 2014, 15 (4); 441-458
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Generalized Kaplan Meier Estimator for Fuzzy Survival Times
Uogólniony estymator Kaplana Meiera dla rozmytego czasu przeżycia
Autorzy:
Shafiq, Muhammad
Viertl, Reinhard
Powiązania:
https://bibliotekanauki.pl/articles/434010.pdf
Data publikacji:
2015
Wydawca:
Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Tematy:
characterizing function
fuzzy numbers
Kaplan Meier estimator
non-precise data
survival time
Opis:
Survival analysis can be defined as a set of methods where the response of interest is the time until a specified event occurred. The most common specified event is death and the related time is called survival time or life time in medical sciences. The Kaplan Meier estimator is one of the popular methods for precise survival times. It is natural that life time is of a continuous nature, therefore it is unrealistic to treat life time observations as precise numbers. In [Viertl 2009] it is shown that life time observations are not precise numbers, but more or less fuzzy. In this study a Generalized Kaplan Meier estimator for fuzzy survival time observations is proposed.
Źródło:
Śląski Przegląd Statystyczny; 2015, 13 (19)
1644-6739
Pojawia się w:
Śląski Przegląd Statystyczny
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Scheme for Template Security at Feature Fusion Level in Multimodal Biometric System
Autorzy:
Selwal, A.
Gupta, S. K.
Kumar, S.
Powiązania:
https://bibliotekanauki.pl/articles/102518.pdf
Data publikacji:
2016
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
feature template
biometric data
feature vectors
multimodal biometrics
fuzzy sets
database
feature fusion
Opis:
Biometrics is the science of human recognition by means of their biological, chemical or behavioural traits. These systems are used in many real life applications simply from biometric based attendance system to providing security at a very sophisticated level. A biometric system deals with raw data captured using a sensor and feature template extracted from raw image. One of the challenges being faced by designers of these systems is to secure template data extracted from the biometric modalities of the user and protect the raw images. In order to minimize spoof attacks on biometric systems by unauthorised users one of the solutions is to use multi-biometric systems. Multi-modal biometric system works by using fusion technique to merge feature templates generated from different modalities of the human. In this work, a novel scheme is proposed to secure template during feature fusion level. The scheme is based on union operation of fuzzy relations of templates of modalities during fusion process of multimodal biometric systems. This approach serves dual purpose of feature fusion as well as transformation of templates into a single secured non invertible template. The proposed technique is irreversible, diverse and experimentally tested on a bimodal biometric system comprising of fingerprint and hand geometry. The given scheme results into significant improvement in the performance of the system with lower equal error rate and improvement in genuine acceptance rate.
Źródło:
Advances in Science and Technology. Research Journal; 2016, 10, 31; 23-30
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
New method of selecting efficient project portfolios in the presence of hybrid uncertainty
Autorzy:
Rębiasz, B.
Powiązania:
https://bibliotekanauki.pl/articles/406365.pdf
Data publikacji:
2016
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
portfolio selection
data processing
hybrid uncertainty
random fuzzy sets
Opis:
A new methods of selecting efficient project portfolios in the presence of hybrid uncertainty has been presented. Pareto optimal solutions have been defined by an algorithm for generating project portfolios. The method presented allows us to select efficient project portfolios taking into account statistical and economic dependencies between projects when some of the parameters used in the calculation of effectiveness can be expressed in the form of an interactive possibility distribution and some in the form of a probability distribution. The procedure for processing such hybrid data combines stochastic simulation with nonlinear programming. The interaction between data are modeled by correlation matrices and the interval regression. Economic dependences are taken into account by the equations balancing the production capacity of the company. The practical example presented indicates that an interaction between projects has a significant impact on the results of calculations.
Źródło:
Operations Research and Decisions; 2016, 26, 4; 65-90
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Improvement of good seamanship using specialized processes and algorithms onboard ships, in fleet operation centers, and in simulations
Autorzy:
Przeniosło, Łukasz
Peschke, Jörg
Hering, Jörg
Powiązania:
https://bibliotekanauki.pl/articles/135627.pdf
Data publikacji:
2020
Wydawca:
Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:
good seamanship
fuzzy logic
holistic algorithms
data fusion
maritime risk
vessels safety
Opis:
The recent rapid improvement of nautical equipment functionality allows one to better observe and predict the dangers related to seamanship. However, these new features come with added complexity, and large amounts of information can overwhelm vessel crews and fleet operation centers, and the current state-of-the-art tools cannot filter out only the most important data for a given time and location. This paper presents the concepts and the algorithms of a software suite that provides a user with problem-oriented advice about a particular risk endangering a vessel and its crew. Based on the calculated navigational dangers and their predicted development, actionable guidance is proposed in an easy-to-understand human language. The quality of good seamanship is improved by a holistic approach to vessel installation, automated fleet operation center priority queuing, and the evaluation of crew performance during simulator training and daily operations. Both the software user interface, as well as the insights provided by the algorithm, are discussed.
Źródło:
Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2020, 61 (133); 83-88
1733-8670
2392-0378
Pojawia się w:
Zeszyty Naukowe Akademii Morskiej w Szczecinie
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new mechanism for data visualization with TSK-type preprocessed collaborative fuzzy rule based system
Autorzy:
Prasad, M.
Liu, Y.-T.
Li, D.-L.
Lin, C. -T.
Shah, R. R.
Kaiwartya, O. P.
Powiązania:
https://bibliotekanauki.pl/articles/91743.pdf
Data publikacji:
2017
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
fuzzy interference system
collaborative clustering
fuzzy logic
big data
data visualization
Opis:
A novel data knowledge representation with the combination of structure learning ability of preprocessed collaborative fuzzy clustering and fuzzy expert knowledge of TakagiSugeno-Kang type model is presented in this paper. The proposed method divides a huge dataset into two or more subsets of dataset. The subsets of dataset interact with each other through a collaborative mechanism in order to find some similar properties within eachother. The proposed method is useful in dealing with big data issues since it divides a huge dataset into subsets of dataset and finds common features among the subsets. The salient feature of the proposed method is that it uses a small subset of dataset and some common features instead of using the entire dataset and all the features. Before interactions among subsets of the dataset, the proposed method applies a mapping technique for granules of data and centroid of clusters. The proposed method uses information of only half or less/more than the half of the data patterns for the training process, and it provides an accurate and robust model, whereas the other existing methods use the entire information of the data patterns. Simulation results show the proposed method performs better than existing methods on some benchmark problems.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2017, 7, 1; 33-46
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Comparison of Fuzzy Clustering Methods for Symbolic Interval-Valued Data
Porównanie metod klasyfikacji rozmytej dla danych symbolicznych interwałowych
Autorzy:
Pełka, Marcin
Dudek, Andrzej
Powiązania:
https://bibliotekanauki.pl/articles/1364881.pdf
Data publikacji:
2015-09-30
Wydawca:
Główny Urząd Statystyczny
Tematy:
spectral clustering
fuzzy clustering
fuzzy partition
interval-valued data
symbolic data analysis
klasyfikacja spektralna
klasyfikacja rozmyta
dane symboliczne interwałowe
analiza danych symbolicznych
Opis:
Interval-valued data can find their practical applications in such situations as recording monthly interval temperatures at meteorological stations, daily interval stock prices, etc. The primary objective of the presented paper is to compare three different methods of fuzzy clustering for interval-valued symbolic data, i.e.: fuzzy c-means clustering, adaptive fuzzy c-means clustering and fuzzy k-means clustering with fuzzy spectral clustering. Fuzzy spectral clustering combines both spectral and fuzzy approaches in order to obtain better results (in terms of Rand index for fuzzy clustering). The conducted simulation studies with artificial and real data sets confirm both higher usefulness and more stable results of fuzzy spectral clustering method, as compared to other existing fuzzy clustering methods for symbolic interval-valued data, when dealing with data featuring different cluster structures, noisy variables and/or outliers.
Dane symboliczne interwałowe mogą znaleźć zastosowanie w wielu sytuacjach – np. w przypadku notowań giełdowych, zmianach kursów walut, itp. Celem artykułu jest porównanie trzech metod klasyfikacji rozmytej dla danych symbolicznych interwałowych – tj. rozmytej klasyfikacji c-średnich, adaptacyjnej rozmytej klasyfikacji c-średnich oraz rozmytej klasyfikacji k-średnich z rozmytą klasyfikacją spektralną. Rozmyta klasyfikacja spektralna stanowi połączenie podejścia spektralnego oraz klasyfikacji rozmytej c-średnich, dzięki czemu możliwe jest otrzymanie lepszych rezultatów (w sensie indeksu Randa dla klasyfikacji rozmytych). Przeprowadzone badania symulacyjne wskazują, że rozmyta klasyfikacja spektralna dla danych symbolicznych pozwala na uzyskanie lepszych wyników niż inne rozmyte metody klasyfikacji dla tego typu danych jeżeli weźmiemy pod uwagę zbiory danych o różnej strukturze klas, która dodatkowo jest zniekształcana przez obserwacje odstające lub zmienne zakłócające.
Źródło:
Przegląd Statystyczny; 2015, 62, 3; 301-319
0033-2372
Pojawia się w:
Przegląd Statystyczny
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Architectures of Granular Information and Their Robustness Properties: a Shadowed Sets Approach
Autorzy:
Pedrycz, W.
Powiązania:
https://bibliotekanauki.pl/articles/908294.pdf
Data publikacji:
1999
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
informacja szczegółowa
zbiór rozmyty
dane zaszumione
niepewność
multiplekser
information granulation and information granules
fuzzy sets
shadowed sets
noisy data
uncertainty
generalized multiplexer
switching mechanisms
Opis:
This paper addresses an important issue of information of granulation and relationships between the size of information granules and the ensuing robustness aspects. The use of shadowed sets helps identify and quantify absorption properties of set-based information granules. Discussed is also a problem of determining an optimal level of information granulation arising in the presence of noisy data. The study proposes a new architecture of granular computing involving continuous and granulated variables. Numerical examples are also included.
Źródło:
International Journal of Applied Mathematics and Computer Science; 1999, 9, 2; 435-455
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
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