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Wyświetlanie 1-11 z 11
Tytuł:
Uncertainty in the conjunctive approach to fuzzy inference
Autorzy:
Kudłacik, Przemysław
Powiązania:
https://bibliotekanauki.pl/articles/2055166.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
fuzzy inference
conjunctive approach
fuzzy truth value
wnioskowanie rozmyte
podejście łączne
wartość logiczna rozmyta
Opis:
Fuzzy inference using the conjunctive approach is very popular in many practical applications. It is intuitive for engineers, simple to understand, and characterized by the lowest computational complexity. However, it leads to incorrect results in the cases when the relationship between a fact and a premise is undefined. This article analyses the problem thoroughly and provides several possible solutions. The drawbacks of uncertainty in the conjunctive approach are presented using fuzzy inference based on a fuzzy truth value, first introduced by Baldwin (1979c). The theory of inference is completed with a new truth function named 0-undefined for two-valued logic, which is further generalized into fuzzy logic as α-undefined. Eventually, the proposed modifications allow altering existing implementations of conjunctive fuzzy systems to interpret the undefined state, giving adequate results.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2021, 31, 3; 431--444
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Rule weights in a neuro-fuzzy system with a hierarchical domain partition
Autorzy:
Simiński, K.
Powiązania:
https://bibliotekanauki.pl/articles/907754.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system rozmyty
system wnioskujący
podział hierarchiczny
fuzzy inference system
hierarchical input domain partition
rule weights
Opis:
The paper discusses the problem of rule weight tuning in neuro-fuzzy systems with parameterized consequences in which rule weights and the activation of the rules are not interchangeable. Some heuristic methods of rule weight computation in neuro-fuzzy systems with a hierarchical input domain partition and parameterized consequences are proposed. Several heuristics with experimental results showing the advantage of their usage are presented.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2010, 20, 2; 337-347
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Real–valued GCS classifier system
Autorzy:
Cielecki, Ł.
Unold, O.
Powiązania:
https://bibliotekanauki.pl/articles/929825.pdf
Data publikacji:
2007
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
uczenie maszynowe
wnioskowanie gramatyczne
gramatyka bezkontekstowa
learning classifier systems
GCS
GAs
grammatical inference
context-free grammar
Opis:
Learning Classifier Systems (LCSs) have gained increasing interest in the genetic and evolutionary computation literature. Many real-world problems are not conveniently expressed using the ternary representation typically used by LCSs and for such problems an interval-based representation is preferable. A new model of LCSs is introduced to classify realvalued data. The approach applies the continous-valued context-free grammar-based system GCS. In order to handle data effectively, the terminal rules were replaced by the so-called environment probing rules. The rGCS model was tested on the checkerboard problem.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2007, 17, 4; 539-547
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evolution-fuzzy rule based system with parameterized consequences
Autorzy:
Czekalski, P.
Powiązania:
https://bibliotekanauki.pl/articles/908394.pdf
Data publikacji:
2006
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
strategia ewolucyjna
system rozmyty
system hybrydowy
evolutionary strategy
fuzzy inference system
off-line learning
hybrid system
Opis:
While using automated learning methods, the lack of accuracy and poor knowledge generalization are both typical problems for a rule-based system obtained on a given data set. This paper introduces a new method capable of generating an accurate rule-based fuzzy inference system with parameterized consequences using an automated, off-line learning process based on multi-phase evolutionary computing and a training data covering algorithm. The presented method consists of the following steps: obtaining an initial set of rules with parameterized consequences using the Michigan approach combined with an evolutionary strategy and a covering algorithm for the training data set; reducing the obtained rule base using a simple genetic algorithm; multi-phase tuning of the fuzzy inference system with parameterized consequences using the Pittsburgh approach and an evolutionary strategy. The paper presents experimental results using popular benchmark data sets regarding system identification and time series prediction, providing a reliable comparison to other learning methods, particularly those based on neuro-fuzzy, clustering and \epsilon-insensitive methods. An examplary fuzzy inference system with parameterized consequences using the Reichenbach implication and the minimum t-norm was implemented to obtain numerical results.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2006, 16, 3; 373-385
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Decomposition of the fuzzy inference system for implementation in the FPGA structure
Autorzy:
Wyrwoł, B.
Hrynkiewicz, E.
Powiązania:
https://bibliotekanauki.pl/articles/330759.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
fuzzy logic
fuzzy inference algorithm
decomposition
digital fuzzy logic controller
FPGA
logika rozmyta
algorytm wnioskowania rozmytego
sterownik rozmyty
Opis:
The paper presents the design and implementation of a digital rule-relational fuzzy logic controller. Classical and decomposed logical structures of fuzzy systems are discussed. The second allows a decrease in the hardware cost of the fuzzy system and in the computing time of the final result (fuzzy or crisp), especially when referring to relational systems. The physical architecture consists of IP modules implemented in an FPGA structure. The modules can be inserted into or removed from the project to get a desirable fuzzy logic controller configuration. The fuzzy inference system implemented in FPGA can operate with a much higher performance than software implementations on standard microcontrollers.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2013, 23, 2; 473-483
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hand gesture recognition based on free-form contours and probabilistic inference
Autorzy:
Kasprzak, W.
Wilkowski, A.
Czapnik, K.
Powiązania:
https://bibliotekanauki.pl/articles/331308.pdf
Data publikacji:
2012
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
śledzenie dłoni
analiza sekwencji obrazów
wnioskowanie stochastyczne
active contours
hand pose detection
hand tracking
image sequence analysis
stochastic inference
Opis:
A computer vision system is described that captures color image sequences, detects and recognizes static hand poses (i.e., 'letters') and interprets pose sequences in terms of gestures (i.e., 'words'). The hand object is detected with a double-active contour-based method. A tracking of the hand pose in a short sequence allows detecting 'modified poses', like diacritic letters in national alphabets. The static hand pose set corresponds to hand signs of a thumb alphabet. Finally, by tracking hand poses in a longer image sequence, the pose sequence is interpreted in terms of gestures. Dynamic Bayesian models and their inference methods (particle filter and Viterbi search) are applied at this stage, allowing a bi-driven control of the entire system.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2012, 22, 2; 437-448
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
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
Artykuł
Tytuł:
A hierarchy of finite state machines as a scenario player in interactive training of pilots in flight simulators
Autorzy:
Bach, Małgorzata
Werner, Aleksandra
Mrozik, Magda
Cyran, Krzysztof A.
Powiązania:
https://bibliotekanauki.pl/articles/2055173.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
Bayesian inference
deterministic Moore machine
flight simulator
finite state machine
scenario player
wnioskowanie Bayesa
automat Moore'a
symulator lotu
automat skończony
Opis:
The paper presents the concept of a control unit, i.e., a scenario player, for interactive training pilots in flight simulators. This scenario player is modelled as a hierarchy of finite state machines. Such an approach makes it possible to separate the details of an augmented reality display device which is used in training, from the core module of the system, responsible for contextual organization of the content. Therefore, the first contribution of this paper is the mathematical model of the scenario player as a universal formulation of the self-trained control unit for interactive learning systems, which is applicable in a variety of situations not limited solely to flight simulator related procedures. The second contribution is an experimental verification achieved by extensive simulations of the model, which proves that the proposed approach is capable to properly self-organize details of the context information by tracing preferences of the end users. For that latter purpose, the original algorithm is derived from statistical analysis, including Bayesian inference. The whole approach is illustrated by a real application of training the preflight procedure for the captain of the Boeing 737 aircraft in a flight simulator.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2021, 31, 4; 713--727
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A hierarchical inferential method for indoor scene classification
Autorzy:
Jiang, J.
Liu, P.
Ye, Z.
Zhao, W.
Tang, X.
Powiązania:
https://bibliotekanauki.pl/articles/330842.pdf
Data publikacji:
2017
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
indoor scene classification
semantic hierarchical structure
rule based inference
Markov logic network
struktura hierarchiczna
regułowy system wnioskowania
sieć logiczna Markova
Opis:
Indoor scene classification forms a basis for scene interaction for service robots. The task is challenging because the layout and decoration of a scene vary considerably. Previous studies on knowledge-based methods commonly ignore the importance of visual attributes when constructing the knowledge base. These shortcomings restrict the performance of classification. The structure of a semantic hierarchy was proposed to describe similarities of different parts of scenes in a fine-grained way. Besides the commonly used semantic features, visual attributes were also introduced to construct the knowledge base. Inspired by the processes of human cognition and the characteristics of indoor scenes, we proposed an inferential framework based on the Markov logic network. The framework is evaluated on a popular indoor scene dataset, and the experimental results demonstrate its effectiveness.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2017, 27, 4; 839-852
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of Sensitivity Theory to Fuzzy Logic Based Fdi
Autorzy:
Dalton, T.
Klotzek, P.
Frank, P. M.
Powiązania:
https://bibliotekanauki.pl/articles/908289.pdf
Data publikacji:
1999
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system rozmyty
wyodrębnienie i wykrycie błędu
teoria wrażliwości
analiza reszt
fuzzy systems
fault detection and isolation
fuzzy inference
sensitivity theory
residual analysis
two-tank system
Opis:
This paper describes an application of sensitivity theory to the analysis of a certain class of fuzzy systems which can be used for fault detection and isolation (FDI). The work is divided into three main tasks. The first is the mathematical representation of some class of fuzzy systems. This is followed by an application of sensitivity theory to fuzzy systems based on the approach detailed in the first part. Finally, this method is applied to a fuzzy fault diagnosis scheme for the two-tank system, and the results compared with those achieved by the application of sensitivity theory to a non-fuzzy diagnosis scheme for the same system. Simulation results for the fuzzy and non-fuzzy fault diagnosis schemes are presented, which verify the results obtained via the application of sensitivity theory.
Źródło:
International Journal of Applied Mathematics and Computer Science; 1999, 9, 3; 619-636
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forecasting return products in an integrated forward/reverse supply chain utilizing an ANFIS
Autorzy:
Kumar, D. T.
Soleimani, H.
Kannan, G.
Powiązania:
https://bibliotekanauki.pl/articles/329809.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
artificial neural network
adaptive network based fuzzy
inference system
closed loop supply chain
forecasting methods
fuzzy neural network
sztuczna sieć neuronowa
system wnioskowania
metoda prognozowania
sieć neuronowa rozmyta
Opis:
Interests in Closed-Loop Supply Chain (CLSC) issues are growing day by day within the academia, companies, and customers. Many papers discuss profitability or cost reduction impacts of remanufacturing, but a very important point is almost missing. Indeed, there is no guarantee about the amounts of return products even if we know a lot about demands of first products. This uncertainty is due to reasons such as companies’ capabilities in collecting End-of-Life (EOL) products, customers’ interests in returning (and current incentives), and other independent collectors. The aim of this paper is to deal with the important gap of the uncertainties of return products. Therefore, we discuss the forecasting method of return products which have their own open-loop supply chain. We develop an integrated two-phase methodology to cope with the closed-loop supply chain design and planning problem. In the first phase, an Adaptive Network Based Fuzzy Inference System (ANFIS) is presented to handle the uncertainties of the amounts of return product and to determine the forecasted return rates. In the second phase, and based on the results of the first one, the proposed multi-echelon, multi-product, multi-period, closed-loop supply chain network is optimized. The second-phase optimization is undertaken based on using general exact solvers in order to achieve the global optimum. Finally, the performance of the proposed forecasting method is evaluated in 25 periods using a numerical example, which contains a pattern in the returning of products. The results reveal acceptable performance of the proposed two-phase optimization method. Based on them, such forecasting approaches can be applied to real-case CLSC problems in order to achieve more reliable design and planning of the network.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2014, 24, 3; 669-682
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-11 z 11

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