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Wyświetlanie 1-15 z 58
Tytuł:
Fuzzy multi agent system for automatic classification and negotiation of QOS in cloud computing
Autorzy:
Bakraouy, Zineb
Abbass, Wissam
Baina, Amine
Bellafkih, Mostafa
Powiązania:
https://bibliotekanauki.pl/articles/1837385.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
MAS
SLA
negotiation
QOS
availability
web services
service broker
classification
fuzzy logic
inference system
fuzzy inference system
Opis:
The use of Multi Agents Systems (MAS), Cloud Computing (CC) and Fuzzy Inference System (FIS) in e-commerce has increased in recent years. The purpose of these systems is to enable users of electronic markets to make transactions in the best conditions and to help them in their decisions. The design and implementation is often characterized by the constant manipulation of information, many of which are imperfect. The use of the multi-agent paradigm for the realization of these systems implies the need to integrate mechanisms that take into account the processing of fuzzy information. This makes it necessary to design multi-agent systems (MAS) with fuzzy characteristics. For the modeling and realization of this system, we chose to use the FMAS model. This paper deals with the presentation of the use of the Fuzzy MAS model for the development of a management and decision support application in a virtual market with high availability. After the presentation of the system to be realized in the first section, we describe in the second section the application of the model FMAS for the design and the realization of this system. We then specify the JADE implementation platform and how the fuzzy agents of our model (Expert, Choice and Query) can be implemented using this platform.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 3; 56-64
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of a Fuzzy Inference System for the Optimization of Material Removal Rate and Multiple Surface Roughness Characteristics in the Machining of GFRP Polyester Composites
Autorzy:
Singh, A.
Datta, S.
Mahapatra, S. S.
Powiązania:
https://bibliotekanauki.pl/articles/375921.pdf
Data publikacji:
2013
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
GFRP
DOE
Fuzzy Inference System (FIS)
Taguchi method
Opis:
This paper presents a multi-objective extended optimization methodology applied in the machining of a randomly oriented GFRP rod. Design of Experiment (DOE) has been selected based on a L9 orthogonal array design with varying process control parameters like: spindle speed, feed rate and depth of cut. Multiple surface roughness parameters of the machined FRP product along with the Material Removal Rate (MRR) of the machining process have been optimized simultaneously. The Fuzzy Inference System (FIS) has been proposed for providing feasible means for the meaningful aggregation of multiple objective unctions into an equivalent single performance index (MPCI). This Multi-Performance Characteristic Index (MPCI) has been optimized using the Taguchi method. The approach adapted here is capable of overcoming limitations/assumptions of existing optimization methodologies available in the literature.
Źródło:
Decision Making in Manufacturing and Services; 2013, 7, 1-2; 19-42
1896-8325
2300-7087
Pojawia się w:
Decision Making in Manufacturing and Services
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Two Extensions of Trust Management Languages
Autorzy:
Felkner, Anna
Powiązania:
https://bibliotekanauki.pl/articles/307850.pdf
Data publikacji:
2020
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
access control
conditional credentials
inference system with time constraints
Opis:
This article is focused on the family of role-based trust management languages (RT). Trust management languages are a useful method of representing security credentials and policies in large distributed access control mechanisms. They provide sets of credentials that are assigned to individual roles performed by the specific entities. These credentials provide relevant information about security policies issued by trusted authorities and define user permissions. RT languages describe the individual entities and the roles that these entities play in a given environment. A set of credentials representing a given security policy defines which entity has the necessary rights to access a specific resource and which entity does not have such rights. This study presents the results of research focusing on the potential of the family of RT languages. Its purpose is to show how security policies may be applied more widely by applying an inference system, and then using the extensions of the credentials, by taking into account time-related information or the conditions imposed with regard to the validity of such credentials. Each of these extensions can be used jointly or separately, offering even a wider range of opportunities.
Źródło:
Journal of Telecommunications and Information Technology; 2020, 1; 87-94
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy system modelling to assess water quality for irrigation purposes
Autorzy:
Hamdan, Ahmed Naseh Ahmed
Al Saad, Zainb A. A.
Abu-Alhail, Saad
Powiązania:
https://bibliotekanauki.pl/articles/1841962.pdf
Data publikacji:
2021
Wydawca:
Instytut Technologiczno-Przyrodniczy
Tematy:
Fuzzy Inference System
irrigation water quality
Richard diagram
sodium adsorption ratio
Opis:
This study attempts to find a fuzzy logic system for assessing the quality of water in water treatment plants (WTPs) providing water for irrigation purposes in the Basrah Governorate (South of Iraq). Each month, samples are taken in each of six major WTPs to measure electrical conductivity (EC), and the content of sodium, magnesium and calcium. The calculated value which is the sodium adsorption ratio (SAR) is plotted with EC on the Richard diagram. SAR and EC values are combined together in a fuzzy inference system (FIS) to find out a quality number called the fuzzy irrigation water quality index number (FIWQI) which ranges from zero to one. The higher the value of the index, the better water quality. The Richard diagram, which helps to classify irrigation water, is used to adjust FIS components. Results show that the FIWQI for all WTPs changes depending on location and season. It ranges between 0.114–0.170, 0.120–0.190, 0.114–0.170, 0.114–0.202, 0.118–0.500 and 0.46–0.500 for Al-Bradhaia 1, Al-Jubaila 1, Shatt Al-Arab, Garmmah 1, Al-Rebat, and Old Shauaibah WTPs, respectively. The results indicate that WTPs effluent drawn from the Shatt Al-Arab River has poor water quality for irrigation purposes, except for an Old Shauaibah which receives water from another source called a sweet water canal. FIS results are compared with values obtained from the Richard diagram and 96% degree of compatibility between the two methods is attained. This indicates that FIS is an acceptable method for water quality classification.
Źródło:
Journal of Water and Land Development; 2021, 50; 98-107
1429-7426
2083-4535
Pojawia się w:
Journal of Water and Land Development
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wybrane metody sztucznej inteligencji zaimplementowane w języku programowania C/C++
Selected methods of artificial intelligence implemented in C/C++ programming language
Autorzy:
Mreła, Aleksandra
Powiązania:
https://bibliotekanauki.pl/articles/41206422.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Kazimierza Wielkiego w Bydgoszczy
Tematy:
edukacja
logika rozmyta
systemy wnioskujące
C++
education
fuzzy logic
inference system
Opis:
Obecnie coraz częściej wykorzystuje się metody sztucznej inteligencji (AI) do budowania systemów ekspertowych, czy opartych na wiedzy. Jednakże, bardzo często podczas zajęć w szkole podstawowej i średniej podczas zajęć z programowania, lub ogólniej kształcenia myślenia komputacyjnego, uczniowie uczą się algorytmów rozwiązujących problemy w warunkach pewności. Wobec tego większość młodych ludzi nie ma okazji rozważania rozwiązań problemów w zakresie logiki rozmytej. Aby nauczyciele informatyki rozważali z uczniami metody sztucznej inteligencji, należy przygotować proste przykłady algorytmów AI. W artykule przedstawiono kilka prostych przykładów zbiorów i relacji rozmytych oraz prostego systemu wnioskującego zakodowanych w C++.
Currently, artificial intelligence (AI) methods are increasingly used to build expert or knowledge-based systems. However, very often during elementary and high school classes while programming classes, or more general, computational thinking training, students learn algorithms that solve problems in conditions of certainty. Therefore, most young people have no opportunity to consider solutions to fuzzy logic problems. For IT teachers to discuss artificial intelligence methods with students, simple AI algorithms should be prepared. The article presents some simple examples of fuzzy sets and relations as well as a simple inference system coded in C++.
Źródło:
Studia i Materiały Informatyki Stosowanej; 2019, 1; 11-13
1689-6300
Pojawia się w:
Studia i Materiały Informatyki Stosowanej
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:
Two semantics of trust management language with negation
Autorzy:
Felkner, A.
Powiązania:
https://bibliotekanauki.pl/articles/308637.pdf
Data publikacji:
2013
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
access control
inference system
monotonicity
role-based trust management
set-theoretic semantics
Opis:
The family of Role-based Trust management languages is used for representing security policies by defining a formalism, which uses credentials to handle trust in decentralized, distributed access control systems. A credential provides information about the privileges of users and the security policies issued by one or more trusted authorities. The main topic of this paper is RT⊖, a language which provides a carefully controlled form of non-monotonicity. The core part of the paper defines two different semantics of RT⊖ language – a relational, set-theoretic semantics for the language, and an inference system, which is a kind of operational semantics. The set-theoretic semantics maps roles to a set of entity names. In the operational semantics credentials can be derived from an initial set of credentials using a set of inference rules. The soundness and the completeness of the inference system with respect to the set-theoretic semantics of RT⊖ will be proven.
Źródło:
Journal of Telecommunications and Information Technology; 2013, 4; 102-108
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
FLC control for tuning exploration phase in bio-inspired metaheuristic
Autorzy:
Kiełkowicz, K.
Grela, D.
Powiązania:
https://bibliotekanauki.pl/articles/106299.pdf
Data publikacji:
2016
Wydawca:
Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:
Bat algorithm
swarm intelligence
metaheuristics
optimization
fuzzy logic
Mamdami-Type inference system
Opis:
Growing popularity of the Bat Algorithm has encouraged researchers to focus their work on its further improvements. Most work has been done within the area of hybridization of Bat Algorithm with other metaheuristics or local search methods. Unfortunately, most of these modifications not only improves the quality of obtained solutions, but also increases the number of control parameters that are needed to be set in order to obtain solutions of expected quality. This makes such solutions quite impractical. What more, there is no clear indication what these parameters do in term of a search process. In this paper authors are trying to incorporate Mamdani type Fuzzy Logic Controller (FLC) to tackle some of these mentioned shortcomings by using the FLC to control the exploration phase of a bio-inspired metaheuristic. FLC also allows us to incorporate expert knowledge about the problem at hand and define expected behaviors of system – here process of searching in multidimensional search space by modeling the process of bats hunting for their prey.
Źródło:
Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica; 2016, 16, 2; 32-38
1732-1360
2083-3628
Pojawia się w:
Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forecasting the Flow Coefficient of the River Basin Using Adaptive Fuzzy Inference System and Fuzzy SMRGT Method
Autorzy:
Gunal, Ayse Yeter
Mehdi, Ruya
Powiązania:
https://bibliotekanauki.pl/articles/27323840.pdf
Data publikacji:
2023
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
ANFIS
adaptive neuro-fuzzy inference system
SMRGT
flow coefficient
fuzzy logic
surface water
Opis:
In hydrology and water resources engineering, predicting the flow coefficient is a crucial task that helps estimate the precipitation resulting in a surface flow. Accurate flow coefficient prediction is essential for efficient water management, flood control strategy development, and water resource planning. This investigation calculated the flow coefficient using models based on Simple Membership functions and fuzzy Rules Generation Technique (SMRGT) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) model. The fuzzy logic methods are used to model the intricate connections between the inputs and the output. Statistical parameters such as the coefficient of determination (R2), the root mean square error (RMSE), the mean absolute error (MAE), and the mean absolute percentage error (MAPE) were used to evaluate the performance of models. The statistical tests outcome for the SMRGT model was (RMSE:0.056, MAE:1.92, MAPE:6.88, R2:0.996), and for the ANFIS was (RMSE:0.96, MAE:2.703, MAPE:19.97, R2:0.8038). According to the findings, the SMRGT, a physics-based model, exhibited superior accuracy and reliability in predicting the flow coefficient compared to ANFIS. This is attributed to the SMRGT’s ability to integrate expert knowledge and domain-specific information, rendering it a viable solution for diverse issues.
Źródło:
Journal of Ecological Engineering; 2023, 24, 7; 96--107
2299-8993
Pojawia się w:
Journal of Ecological Engineering
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:
Project Risk Assessment Using Fuzzy Inference System
Autorzy:
Pisz, Iwona
Powiązania:
https://bibliotekanauki.pl/articles/503848.pdf
Data publikacji:
2011
Wydawca:
Międzynarodowa Wyższa Szkoła Logistyki i Transportu
Tematy:
project
risk
risk management
risk assessment
fuzzy sets
fuzzy numbers
Fuzzy Inference System
Opis:
The article focuses on the risk assessment of project. The risk assessment is a complexity decision making problem. The assessment risk of projects can be solved with Fuzzy Sets Theory. A Fuzzy Inference System is presented in order to risk assessment of the given project.
Źródło:
Logistics and Transport; 2011, 13, 2; 25-34
1734-2015
Pojawia się w:
Logistics and Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Active Noise Control Using a Fuzzy Inference System Without Secondary Path Modelling
Autorzy:
Kurczyk, S.
Pawelczyk, M.
Powiązania:
https://bibliotekanauki.pl/articles/177155.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
active noise control
adaptive control
fuzzy inference system
FXLMS
sign varying step size
Opis:
For many adaptive noise control systems the Filtered-Reference LMS, known as the FXLMS algorithm is used to update parameters of the control filter. Appropriate adjustment of the step size is then important to guarantee convergence of the algorithm, obtain small excess mean square error, and react with required rate to variation of plant properties or noise nonstationarity. There are several recipes presented in the literature, theoretically derived or of heuristic origin. This paper focuses on a modification of the FXLMS algorithm, were convergence is guaranteed by changing sign of the algorithm steps size, instead of using a model of the secondary path. A Takagi-Sugeno-Kang fuzzy inference system is proposed to evaluate both the sign and the magnitude of the step size. Simulation experiments are presented to validate the algorithm and compare it to the classical FXLMS algorithm in terms of convergence and noise reduction.
Źródło:
Archives of Acoustics; 2014, 39, 2; 243-248
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy inference method for intelligent artificial system
Autorzy:
Cho, Y. I.
Powiązania:
https://bibliotekanauki.pl/articles/332987.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
systemy rozmyte
system MAX-MIN
sztuczna inteligencja
fuzzy inference system
MAX-MIN system
artificial intelligence control
Opis:
A fuzzy control system which is a typical system utilizing fuzzy model is mainly using the Max-Min CRI (Compositional Rule of Inference) method by Zadeh and Mamdani for fuzzy inference. But the Max-Min CRI method suffers from drawbacks including: error-prone weighting strategy, inefficient compositional rule of inference, and subjective formulation of membership functions. Because of these problems in the Max-Min CRI method, the inference often results in significant error regions specifying the difference between the desired outputs and the inferred outputs. To overcome such problems, we propose here a new fuzzy inference system for artificial intelligence control.
Źródło:
Journal of Medical Informatics & Technologies; 2009, 13; 11-14
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Prediction of littoral drift with adaptive neuro-fuzzy inference system
Ocena dryfu morskiego z wykorzystaniem systemu ANFIS [Adaptive Neuro-Fuzzy Inference System]
Autorzy:
Sabet, M S
Naseri, M.A.
Sabet, H.S.
Powiązania:
https://bibliotekanauki.pl/articles/81613.pdf
Data publikacji:
2010
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Tematy:
littoral sand drift
coastal zone
adaptive neuro-fuzzy inference system
validation
physical process
database
Opis:
The amount of sand moving parallel to a coastline forms a prerequisite for many harbor design projects. Such information is currently obtained through various empirical formulae. Despite so many works in the past, an accurate and reliable estimation of the rate of sand drift has still remained a problem. It is a non-linear process and can be described by chaotic time-series. The current study addresses this issue through the use of Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS is about taking an initial fuzzy inference system (FIS) and tuning it with a back propagation algorithm based on the collection of input-output data. ANFIS was developed to predict the sand drift from a variety of causative variables. The structure and algorithm of ANFIS for predicting the rate of sand drift is described. The Adaptive Neuro-Fuzzy Inference System was validated by confi rming its consistency with a database of specifi ed physical process.
W artykule przedstawiono adaptację systemu ANFIS do oceny wielkości dryfu fal piaskowych poruszających się wzdłuż wybrzeża morskiego. Pomimo wielu informacji o charakterze ilościowym oraz jakościowym zebranych w badaniach terenowych oraz opracowanych wzorów empirycznych opisujących analizowane zjawisko, autorzy widzą potrzebę stosowania symulacji zjawiska za pomocą metod numerycznych. Takie możliwości daje omówiony w pracy system ANFIS.
Źródło:
Annals of Warsaw University of Life Sciences - SGGW. Land Reclamation; 2010, 42, 1; 159-167
0208-5771
Pojawia się w:
Annals of Warsaw University of Life Sciences - SGGW. Land Reclamation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy inference system and prediction
Autorzy:
Žák, L.
Valliš, D.
Powiązania:
https://bibliotekanauki.pl/articles/1818737.pdf
Data publikacji:
2015
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
fuzzy sets
fuzzy logic
fuzzy inference system
prediction implementation
employees
zbiory rozmyte
logika rozmyta
system wnioskowania rozmyty
pracownicy
Opis:
This paper describes the implementation of fuzzy set theory and Fuzzy Inference System (FIS) for prediction of electric load. The proposed technique utilizes fuzzy rules to incorporate historical weather and load data. The use of fuzzy logic effectively handles the load variations due to special events. The fuzzy logic has been extensively tested on actual data obtained from the Czech Electric Power Company (ˇCEZ) for 24-hour ahead prediction. Test results indicate that the fuzzy rule base can produce results better in accuracy than artificial neural networks (ANNs) method.
Źródło:
Journal of TransLogistics; 2015, 1, 1; 193--202
2450-5870
Pojawia się w:
Journal of TransLogistics
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 58

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