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Wyszukujesz frazę "fuzzy rule" wg kryterium: Temat


Tytuł:
On wavelet based enhancing possibilities of fuzzy classification methods
Autorzy:
Lilik, Ferenc
Solecki, Levente
Sziová, Brigita
Kóczy, László T.
Nagy, Szilvia
Powiązania:
https://bibliotekanauki.pl/articles/384751.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
fuzzy classification
wavelet analysis
fuzzy rule interpolation
structural entropy
Opis:
If the antecedents of a fuzzy classification method are derived from pictures or measured data, it might have too many dimensions to handle. A classification scheme based on such data has to apply a careful selection or processing of the measured results: either a sampling, re‐ sampling is necessary. or the usage of functions, transfor‐ mations that reduce the long, high dimensional observed data vector or matrix into a single point or to a low num‐ ber of points. Wavelet analysis can be useful in such cases in two ways. As the number of resulting points of the wavelet ana‐ lysis is approximately half at each filters, a consecutive application of wavelet transform can compress the me‐ asurement data, thus reducing the dimensionality of the signal, i.e., the antecedent. An SHDSL telecommunication line evaluation is used to demonstrate this type of appli‐ cability, wavelets help in this case to overcome the pro‐ blem of a one dimensional signal sampling. In the case of using statistical functions, like mean, variance, gradient, edge density, Shannon or Rényi en‐ tropies for the extraction of the information from a pic‐ ture or a measured data set, and they don not produce enough information for performing the classification well enough, one or two consecutive steps of wavelet analy‐ sis and applying the same functions for the thus resulting data can extend the number of antecedents, and can dis‐ till such parameters that were invisible for these functi‐ ons in the original data set. We give two examples, two fuzzy classification schemes to show the improvement caused by wavelet analysis: a measured surface of a com‐ bustion engine cylinder and a colonoscopy picture. In the case of the first example the wear degree is to be deter‐ mine, in the case of the second one, the roundish polyp content of the picture. In the first case the applied statisti‐ cal functions are Rényi entropy differences, the structural entropies, in the second case mean, standard deviation, Canny filtered edge density, gradients and the entropies. In all the examples stabilized KH rule interpolation was used to treat sparse rulebases.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 2; 32-41
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Towards a linguistic description of dependencies in data
Autorzy:
Batyrshin, I.
Wagenknecht, M.
Powiązania:
https://bibliotekanauki.pl/articles/908041.pdf
Data publikacji:
2002
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
informatyka
fuzzy approximation
linguistic term
fuzzy rule
genetic algorithm
Opis:
The problem of a linguistic description of dependencies in data by a set of rules Rk: "If X is Tk then Y is Sk" is considered, where Tk's are linguistic terms like SMALL, BETWEEN 5 AND 7 describing some fuzzy intervals Ak. Sk's are linguistic terms like DECREASING and QUICKLY INCREASING describing the slopes pk of linear functions yk=pkx +qk approximating data on Ak. The decision of this problem is obtained as a result of a fuzzy partition of the domain X on fuzzy intervals Ak, approximation of given data {xi,yi}, i=1,...,n by linear functions yk=pkx+qk on these intervals and by re-translation of the obtained results into linguistic form. The properties of the genetic algorithm used for construction of the optimal partition and several methods of data re-translation are described. The methods are illustrated by examples, and potential applications of the proposed methods are discussed.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2002, 12, 3; 391-401
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Automatic generation of fuzzy inference systems using heuristic possibilistic clustering
Autorzy:
Viattchenin, D. A.
Powiązania:
https://bibliotekanauki.pl/articles/384377.pdf
Data publikacji:
2010
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
possibilistic clustering
fuzzy cluster
typical point
tolerance threshold
fuzzy rule
Opis:
The interpretability and flexibility of fuzzy classification rules make them a popular basis for fuzzy controllers. Fuzzy control methods constitute a part of the areas of automation and robotics. The paper deals with the method of extracting fuzzy classification rules based on a heuristic method of possibilistic clustering. The description of basic concepts of the heuristic method of possibilistic clustering based on the allotment concept is provided. A general plan of the D-AFC(c)-algorithm is also given. A method of constructing and tuning of fuzzy rules based on clustering results is proposed. An illustrative example of the method's application to the Anderson's Iris data is carried out. An analysis of the experimental results is given and preliminary conclusions are formulated.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2010, 4, 3; 36-44
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Extracting fuzzy classifications rules from three - way data
Autorzy:
Kacprzyk, J.
Owsinski, J. W.
Viattchenin, D. A.
Powiązania:
https://bibliotekanauki.pl/articles/385102.pdf
Data publikacji:
2014
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
three-way data
possibilistic clustering
fuzzy cluster
typical point
fuzzy rule
Opis:
The paper deals in the conceptual way with the problem of extracting fuzzy classification rules from the three-way data meant in the sense of Sato and Sato [7]. A novel technique based on a heuristic method of possibilistic clustering is proposed. A description of basic concepts of a heuristic method of possibilistic clustering based on concept of an allotment is provided. A preprocessing technique for three-way data is shown. An extended method of constructing fuzzy classification rules based on clustering results is proposed. An illustrative example of the method’s application to the Sato and Sato’s data [7] is provided. An analysis of the experimental results obtained with some conclusions are given.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2014, 8, 2; 47-57
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
IoT & WSN based Smart Precision Agriculture
Autorzy:
Jayashree, M. M.
Sangeetha, S.
Powiązania:
https://bibliotekanauki.pl/articles/1193585.pdf
Data publikacji:
2016
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
Fuzzy Rule-base
Internet of Things
IoT
Prediction
WSN
Opis:
Now a days, agriculture plays a vital role in Indian economy. Agriculture gets destroyed due to fewer numbers of workers and animal intrusions in the field. So, Agricultural lands are becoming plots. The main objective is to improve the sustainable agriculture by enhancing the technology using wireless sensor technology. Wireless sensor networks and IoT plays a major role in Smart agriculture. IoT attach the sensed values with the internet. WSN involves two levels of prediction such as climate and crop. Temperature, Humidity and pH sensors are used to obtain the characteristic data from the land. Based on temperature and humidity, climate is predicted using fuzzy rules. From the predicted climate and using pH value of the soil, the crop to be grown is predicted. The corresponding decisions sent to the respective land owner’s. The sensors are co-ordinated using the GPS and are connected to the base station in an ad-hoc network using WLAN.
Źródło:
World Scientific News; 2016, 41; 261-266
2392-2192
Pojawia się w:
World Scientific News
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Assessment of economic activity of the company on the base of fuzzy inference rules
Autorzy:
Chojnacki, A.
Borzęcka, H.
Powiązania:
https://bibliotekanauki.pl/articles/92954.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
fuzzy sets theory
fuzzy logic
fuzzy rule of conclusion
linguistic variables
fuzzy model of assessment
Opis:
The article presents the assessment of companies efficiency, the idea based on the fuzzy set theory and fuzzy logic. Relevant financial measures are selected by experts and auditors. Variables of the proposed fuzzy model are expressed as linguistic variables and their correlations are defined by If-Then fuzzy rules of conclusion. The theoretical modeling is then followed by numerical examples. There is further extension of model toward assessment and comparison for enterprises of different size and various business branches.
Źródło:
Studia Informatica : systems and information technology; 2009, 1(12); 33-45
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Motion prediction of moving objects in a robot navigational environment using fuzzy-based decision tree approach
Autorzy:
Rajpurohit, V. S.
Manohara Pai, M. M.
Powiązania:
https://bibliotekanauki.pl/articles/384387.pdf
Data publikacji:
2010
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
short term motion prediction
fuzzy rule base
rule base optimization
fuzzy predictor algorithm
directional space approach
decision tree approach
Opis:
In a dynamic robot navigation system the robot has to avoid both static and dynamic objects on its way to destination. Predicting the next instance position of a moving object in a navigational environment is a critical issue as it involves uncertainty. This paper proposes a fuzzy rulebased motion prediction algorithm for predicting the next instance position of moving human motion patterns. Fuzzy rule base has been optimized by directional space approach and decision tree approach. The prediction algorithm is tested for real-life bench- marked human motion data sets and compared with existing motion prediction techniques. Results of the study indicate that the performance of the predictor is comparable to the existing prediction methods.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2010, 4, 4; 11-18
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy model for the information and decision making support system for the CFM branch company
Autorzy:
Walaszek-Babiszewska, A.
Chudzicki, M.
Powiązania:
https://bibliotekanauki.pl/articles/118161.pdf
Data publikacji:
2006
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
managerial decisions
fuzzy rule-based model
car fleet management
MIS
application requirements
customer segmentation
Opis:
The aim of this work is to present the ways of improvement the management process in the CFM company, by developing and implementing the Management Information System (MIS). In the first chapter the characteristic of Car Fleet Management company is presented. The second chapter describes how MIS could support management of that type of company, as well as general and functional requirements of the computer application. Third chapter presents an example of methodology of solving selected decision-making problem using a fuzzy rule-based model.
Źródło:
Applied Computer Science; 2006, 2, 1; 110-121
1895-3735
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Rough Set-Based Dimensionality Reduction for Supervised and Unsupervised Learning
Autorzy:
Shen, Q.
Chouchoulas, A.
Powiązania:
https://bibliotekanauki.pl/articles/908369.pdf
Data publikacji:
2001
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
baza wiedzy
gromadzenie wiedzy
knowledge-based systems
fuzzy rule induction
rough dimensionality reduction
knowledge acquisition
Opis:
The curse of dimensionality is a damning factor for numerous potentially powerful machine learning techniques. Widely approved and otherwise elegant methodologies used for a number of different tasks ranging from classification to function approximation exhibit relatively high computational complexity with respect to dimensionality. This limits severely the applicability of such techniques to real world problems. Rough set theory is a formal methodology that can be employed to reduce the dimensionality of datasets as a preprocessing step to training a learning system on the data. This paper investigates the utility of the Rough Set Attribute Reduction (RSAR) technique to both supervised and unsupervised learning in an effort to probe RSAR's generality. FuREAP, a Fuzzy-Rough Estimator of Algae Populations, which is an existing integration of RSAR and a fuzzy Rule Induction Algorithm (RIA), is used as an example of a supervised learning system with dimensionality reduction capabilities. A similar framework integrating the Multivariate Adaptive Regression Splines (MARS) approach and RSAR is taken to represent unsupervised learning systems. The paper describes the three techniques in question, discusses how RSAR can be employed with a supervised or an unsupervised system, and uses experimental results to draw conclusions on the relative success of the two integration efforts.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2001, 11, 3; 583-601
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new approach for the clustering using pairs of prototypes
Autorzy:
Jezewski, M.
Czabanski, R.
Leski, J.
Horoba, K.
Powiązania:
https://bibliotekanauki.pl/articles/333693.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
fuzzy clustering
pairs of prototypes
fuzzy rule-based classification
grupowanie rozmyte
pary prototypów
rozmyta klasyfikacja oparta na regułach
Opis:
In the presented work two variants of the fuzzy clustering approach dedicated for determining the antecedents of the rules of the fuzzy rule-based classifier were presented. The main idea consists in adding additional prototypes (’prototypes in between’) to the ones previously obtained using the fuzzy c-means method (ordinary prototypes). The ’prototypes in between’ are determined using pairs of the ordinary prototypes, and the algorithm based on distances and densities finding such pairs was proposed. The classification accuracy obtained applying the presented clustering approaches was verified using six benchmark datasets and compared with two reference methods.
Źródło:
Journal of Medical Informatics & Technologies; 2015, 24; 113-121
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The application of the fuzzy rule-based Bayesian algorithm to determine which residential appliances can be considered for the demand response program
Autorzy:
Kapler, Piotr
Powiązania:
https://bibliotekanauki.pl/articles/27311421.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
demand response
residential power consumers
uncertainty
fuzzy rule-based Bayesian
reagowanie na popyt
niepewność
odbiorcy energii lokalni
algorytmy bayesowskie
Opis:
This paper proposes the usage of the fuzzy rule-based Bayesian algorithm to determine which residential appliances can be considered for the Demand Response program. In contrast with other related studies, this research recognizes both randomness and fuzziness in appliance usage. Moreover, the input data for usage prediction consists of nodal price values (which represent the actual power system conditions), appliance operation time, and time of day. The case study of residential power consumer behavior modeling was implemented to show the functionality of the proposed methodology. The results of applying the suggested algorithm are presented as colored 3D control surfaces. In addition, the performance of the model was verified using R squared coefficient and root mean square error. The conducted studies show that the proposed approach can be used to predict when the selected appliances can be used under specific circumstances. Research of this type may be useful for evaluation of the demand response programs and support residential load forecasting.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 4; art. no. e146106
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Handling fuzzy systems’ accuracy-interpretability trade-off by means of multi-objective evolutionary optimization methods – selected problems
Autorzy:
Gorzałczany, M. B.
Rudziński, F.
Powiązania:
https://bibliotekanauki.pl/articles/199824.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
accuracy and interpretability of fuzzy rule-based systems
multi-objective evolutionary optimization
genetic computations
fuzzy systems
dokładność systemów rozmytych
optymalizacja
obliczenia genetyczne
systemy rozmyte
Opis:
The paper addresses several open problems regarding the automatic design of fuzzy rule-based systems (FRBSs) from data using multi-objective evolutionary optimization algorithms (MOEOAs). In particular, we propose: a) new complexity-related interpretability measure, b) efficient strong-fuzzy-partition implementation for improving semantics-related interpretability, c) special-coding-free implementation of rule base and original genetic operators for its processing, and d) implementation of our ideas in the context of well-known MOEOAs such as SPEA2 and NSGA-II. The experiments demonstrate that our approach is an effective tool for handling FRBSs’ accuracy-interpretability trade-off, i.e, designing FRBSs characterized by various levels of such a trade-off (in particular, for designing highly interpretability-oriented systems of still competitive accuracy).
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2015, 63, 3; 791-798
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sprzętowa realizacja procesu dekompozycji lingwistycznej bazy wiedzy systemu wnioskowania przybliżonego
Hardware Implementation of the Knowledge Base Linguistic Decomposition of the Fuzzy Inference System
Autorzy:
Wyrwoł, B.
Powiązania:
https://bibliotekanauki.pl/articles/155723.pdf
Data publikacji:
2007
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
funkcja przynależności
reguła rozmyta
baza wiedzy
wnioskowanie przybliżone
dekompozycja relacyjna
dekompozycja lingwistyczna
układ reprogramowalny FPGA
membership function
fuzzy rule
fuzzy relation
knowledge base
fuzzy inference
relational decomposition
linguistic decomposition
FPGA
Opis:
Metoda dekompozycji relacji rozmytych M. M. Gupty pozwala ograniczyć nakłady sprzętowe niezbędne w realizacji układowej systemów relacyjnych, jednak charakteryzuje się wysokim nakładem obliczeniowym. Tę niekorzystną własność można wyeliminować poprzez rozszerzenie metody podstawowej na płaszczyznę lingwistyczną. Podejście to pozwala wykorzystać uzyskane wyniki w realizacji zarówno systemów regułowych, relacyjnych, jak i mieszanych. W pracy przedstawiono sprzętowy modułu realizujący proces dekompozycji lingwistycznej bazy wiedzy zaimplementowany w systemie wnioskowania przybliżonego FPGA-FIS.
The hardware cost of the FATI relational fuzzy inference system can be reduced using M. M. Gupta's decomposition technique. It is based at projection operation defined for fuzzy relation. A lot of time is required to compute a global relation and a large memory to store it. In the paper has been proposed a modified M. M. Gupta's decomposition method expanded on linguistic level. It allows reducing hardware cost of the implementation of the FITA or FITA/FATI fuzzy inference systems. It can be implemented as a hardware unit in an FPGA structure to decrease an initialization time of the FPGA-FIS system.
Źródło:
Pomiary Automatyka Kontrola; 2007, R. 53, nr 7, 7; 33-35
0032-4140
Pojawia się w:
Pomiary Automatyka Kontrola
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy estimation of activities duration in construction projects
Rozmyte szacowanie czasów trwania robót budowlanych
Autorzy:
Ibadov, N.
Powiązania:
https://bibliotekanauki.pl/articles/230875.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
roboty budowlane
opóźnienie
czas wykonania
szacowanie
niepewność
zbiór rozmyty
wnioskowanie rozmyte
reguła rozmyta
czynnik opóźniający
construction works
delay
duration of works
estimation
uncertainty
fuzzy set
fuzzy logic
fuzzy rule
delay factor
Opis:
During implementation of construction projects, durations of activities are affected by various factors. Because of this, both during the planning phase of the project as well as the construction phase, managers try to estimate, or predict, the length of any delays that may occur. Such estimates allow for the ability to take appropriate action in terms of planning and management during the execution of construction works. This paper presents the use of the non-deterministic concept for describing the uncertainty of estimating works duration. The concept uses the theory of fuzzy sets. The author describes a method for fuzzy estimations of construction works duration based on the fact that uncertain data is an inherent factor in the conditions of construction projects. An example application of the method is presented. The author shows a fuzzy estimation for the duration of an activity, taking into consideration the distorting influence caused by malfunctioning construction equipment and delivery delays of construction materials.
W czasie realizacji obiektów budowlanych, procesy wykonawcze są narażone na wpływ różnych czynników zakłócających (warunki atmosferyczne, nieterminowość dostaw materiałów, awarie sprzętu, kwalifikacje robotników, zła organizacja robót na budowie itp.). Czynniki te, pomimo świadomości planistów o ich istnieniu, nie zawsze są uwzględniane podczas szacowania czasów wykonania robót na etapie projektowania budowy. Powoduje to różnice pomiędzy oszacowaniami czasów wykonania robót a rzeczywistymi czasami wykonania robót, uzyskanymi podczas realizacji budowy. Trzeba mieć na uwadze, że wiedza planisty (eksperta) na temat czynników zakłócających oraz ich konsekwencjach ma charakter przybliżony i niepewny. Kiedy próbuje się oszacować czasy wykonania robót budowlanych, powstaje problem niemożności wykorzystania metod statystycznych i miary probabilistycznej dla oceny skutków realizacji różnych scenariuszy jednoczesnego oddziaływania różnych czynników na przebieg budowy. Warte rozpatrzenia jest w tym przypadku również wykorzystanie logiki rozmytej i teorii zbiorów rozmytych. W artykule przedstawiono przykład wykorzystania teorię zbiorów rozmytych dla oszacowania rozmytego czasu wykonania roboty budowlanej biorąc pod uwagę wpływy zakłócające spowodowane w skutek awarii sprzętu budowlanego oraz opóźnienia w dostawach materiałów budowlanych.
Źródło:
Archives of Civil Engineering; 2015, 61, 2; 23-34
1230-2945
Pojawia się w:
Archives of Civil Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hybrid Learning of Interval Type-2 Fuzzy Systems Based on Orthogonal Least Squares and Back Propagation for Manufacturing Applications
Autorzy:
Mendez, G.
Hernandez, A.
Powiązania:
https://bibliotekanauki.pl/articles/384517.pdf
Data publikacji:
2008
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
type-2 fuzzy inference systems
type-2 neuro-fuzzy systems
hybrid learning
uncertain rule-based fuzzy logic systems
Opis:
This paper presents a novel learning methodology based on the hybrid algorithm for interval type-2 (IT2) fuzzy logic systems (FLS). Since in the literature only back-propagation method has been proposed for tuning of both antecedent and consequent parameters of type-2 fuzzy logic systems, a hybrid learning algorithm has been developed. The hybrid method uses recursive orthogonal least-squares method for tuning of consequent parameters as well as the back-propagation method for tuning of antecedent parameters. The systems were tested for three types of inputs: a) interval singleton b) interval type-1 (T1) non-singleton, c) interval type-2 non-singleton. The experimental results of the application of the hybrid interval type-2 fuzzy logic systems for scale breaker entry temperature prediction in a real hot strip mill were carried out for three different types of coils. They proved the feasibility of the systems developed here for scale breaker entry temperature prediction. Comparison with type-1 fuzzy logic systems shows that the hybrid learning interval type-2 fuzzy logic systems improve performance in scale breaker entry temperature prediction under the tested condition.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2008, 2, 1; 23-32
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł

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