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Tytuł:
Chosen possibilities of $ \overline{ \epsilon } $-fuzzy boundary elements method application in the analysis of conductivity problems with uncertainties
Autorzy:
Witek, Halina
Witek, Bernard
Powiązania:
https://bibliotekanauki.pl/articles/38705714.pdf
Data publikacji:
2023
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
ɛ-fuzzy boundary element method
ɛ-number
fuzzy boundary element method
heat conduction
temperature distribution
object diagnosis
ɛ-metoda rozmytych elementów brzegowych
metoda rozmytych elementów brzegowych
przewodnictwo cieplne
rozkład temperatury
diagnoza obiektu
Opis:
The paper presents a methodology of solving boundary problems with uncertainty parameters based on the use of interval perturbation numbers. This methodology allows for the analysis of very complex problems with different uncertain parameters. Fuzzy Boundary Element Method (FBEM) using $ \overline{ \epsilon } $-number will be called $ \overline{ \epsilon } $-Fuzzy Boundary Element Method ($ \overline{ \epsilon } $-FBEM). Detailed discussion of the problems of computing and applications will be presented on the example of the fuzzy boundary integral equation arising from the boundary problem for the potential problems with heterogeneous, fuzzy boundary conditions of Dirichlet and Neumann type, fuzzy internal sources, fuzzy boundary and fuzzy fundamental solution. The presented methodology can be used to solve various engineering problems (e.g. in civil engineering, power engineering and others) – e.g. to analyze the temperature distribution in structural elements or elements located in the vicinity of objects or devices. In the latter case the increased temperature may be a symptom of a severe failure (e.g. power transformer overload, overexcitation or a fault) which cannot be tolerated due to the threat to the object and to the entire power system. Proposed method maybe used for electrical equipment diagnosis and in consequence as a power system failure prevention. In this paper calculation methodology is illustrated on the example of an area bounded by a square, on the left boundary of which a certain temperature is set, while on the rest of the boundaries the conditions are equal to zero. A dedicated computer program allows for the calculation of both temperature and temperature derivative for any number of boundary elements using $ \overline{ \epsilon } $-FBEM.
Źródło:
Computer Assisted Methods in Engineering and Science; 2023, 30, 4; 407-426
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy-based firefly and ACO algorithm for densely deployed WSN
Autorzy:
Sharma, Tripti
Mohapatra, Amar Kumar
Tomar, Geetam
Powiązania:
https://bibliotekanauki.pl/articles/38700721.pdf
Data publikacji:
2023
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
clustering
firefly
WSN
ant colony optimization
fuzzy
wireless sensor
healthcare network
FIS
grupowanie
robaczek świętojański
optymalizacja kolonii mrówek
rozmyty
czujnik bezprzewodowy
sieć opieki zdrowotnej
Opis:
Most of the wireless sensor networks (WSNs) used in healthcare and security sectors are affected by the battery constraints, which cause a low network lifetime problem and prevents these networks from achieving their maximum performance. It is anticipated that by combining fuzzy logic (FL) approximation reasoning approach with WSN, the complex behavior of WSN will be easier to handle. In healthcare, WSNs are used to track activities of daily living (ADL) and collect data for longitudinal studies. It is easy to understand how such WSNs could be used to violate people’s privacy. The main aim of this research is to address the issues associated with battery constraints for WSN and resolve these issues. Such an algorithm could be successfully applied to environmental monitoring for healthcare systems where a dense sensor network is required and the stability period should be high.
Źródło:
Computer Assisted Methods in Engineering and Science; 2023, 30, 2; 223-246
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Metody adaptacji systemów wiedzy opartej na zbiorach rozmytych
Methods of adaptation of knowledge systems based on fuzzy sets
Autorzy:
Małolepsza, Olga
Powiązania:
https://bibliotekanauki.pl/articles/41205866.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Kazimierza Wielkiego w Bydgoszczy
Tematy:
zbiory rozmyte
metody adaptacji
funkcja przynależności
sztuczna inteligencja
systemy rozmyte
rozmyte sieci neuronowe
fuzzy sets
adaptation method
membership function
artificial intelligence
fuzzy systems
fuzzy neural networks
Opis:
Metody adaptacji systemów wiedzy opartej na zbiorach rozmytych są bardzo ważnym tematem, ponieważ udoskonalają i optymalizują wydajność systemów rozmytych poprzez właściwą metodę adaptacji. Metoda adaptacji zależy od konkretnego zastosowania, wymagań systemowych, dostępnych danych i dziedziny problemu. W artykule przedstawiono zagadnienia związane ze zbiorami rozmytymi oraz podano przykłady. Ponadto zaprezentowano metody adaptacji systemów wiedzy opartej na zbiorach rozmytych takie jak algorytmy genetyczne, programowanie ewolucyjne, algorytmy uczące się, uczenie przez wzmacnianie oraz adaptację online
Adaptation methods for knowledge systems based on fuzzy sets are a very important topic because they improve and optimize the performance of fuzzy systems through a proper adaptation method. The adaptation method depends on the specific application, system requirements, available data and the problem domain. In this paper, the issues related to fuzzy sets are presented and examples are given. In addition, methods for adaptation of fuzzy set-based knowledge systems such as genetic algorithms, evolutionary programming, learning algorithms, reinforcement learning and online adaptation are presented.
Źródło:
Studia i Materiały Informatyki Stosowanej; 2023, 15, 1; 11-20
1689-6300
Pojawia się w:
Studia i Materiały Informatyki Stosowanej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Bootstrap methods for epistemic fuzzy data
Autorzy:
Grzegorzewski, Przemyslaw
Romaniuk, Maciej
Powiązania:
https://bibliotekanauki.pl/articles/2134054.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
bootstrap method
fuzzy data
fuzzy numbers
hypotheses testing
metoda bootstrap
dane rozmyte
testowanie hipotez
Opis:
Fuzzy numbers are often used for modeling imprecise perceptions of the real-valued observations. Such epistemic fuzzy data may cause problems in statistical reasoning and data analysis. We propose a universal nonparametric technique, called the epistemic bootstrap, which could be helpful when the existing methods do not work or do not give satisfactory results. Besides the simple epistemic bootstrap, we develop its several refinements that aim to reduce the variance in statistical inference. We also perform an extended simulation study to examine statistical properties of the approaches considered. The discussion of the results is supplemented by some hints for practical use.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2022, 32, 2; 285--297
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modelling of Plastic Flow Behaviour of Metals in the Hot Deformation Process Using Artificial Intelligence Methods
Autorzy:
Mrzygłód, Barbara
Łukaszek-Sołek, Aneta
Olejarczyk-Wożeńska, Izabela
Pasierbiewicz, Karolina
Powiązania:
https://bibliotekanauki.pl/articles/2174622.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
hot deformation
Inconel 718
rheological model
forming process
neuro-fuzzy inference system
odkształcanie na gorąco
model reologiczny
proces formowania
Opis:
Hot deformation of metals is a widely used process to produce end products with the desired geometry and required mechanical properties. To properly design the hot forming process, it is necessary to examine how the tested material behaves during hot deformation. Model studies carried out to characterize the behaviour of materials in the hot deformation process can be roughly divided into physical and mathematical simulation techniques. The methodology proposed in this study highlights the possibility of creating rheological models for selected materials using methods of artificial intelligence, such as neuro-fuzzy systems. The main goal of the study is to examine the selected method of artificial intelligence to know how far it is possible to use this method in the development of a predictive model describing the flow of metals in the process of hot deformation. The test material was Inconel 718 alloy, which belongs to the family of austenitic nickel-based superalloys characterized by exceptionally high mechanical properties, physicochemical properties and creep resistance. This alloy is hardly deformable and requires proper understanding of the constitutive behaviour of the material under process conditions to directly enable the optimization of deformability and, indirectly, the development of effective shaping technologies that can guarantee obtaining products with the required microstructure and desired final mechanical properties. To be able to predict the behaviour of the material under non-experimentally tested conditions, a rheological model was developed using the selected method of artificial intelligence, i.e. the Adaptive Neuro-Fuzzy Inference System (ANFIS). The source data used in these studies comes from a material experiment involving compression of the tested alloy on a Gleeble 3800 thermo-mechanical simulator at temperatures of 900, 1000, 1050, 1100, 1150oC with the strain rates of 0.01 - 100 s-1 to a constant true strain value of 0.9. To assess the ability of the developed model to describe the behaviour of the examined alloy during hot deformation, the values of yield stress determined by the developed model (ANFIS) were compared with the results obtained experimentally. The obtained results may also support the numerical modelling of stress-strain curves.
Źródło:
Archives of Foundry Engineering; 2022, 22, 3; 41--52
1897-3310
2299-2944
Pojawia się w:
Archives of Foundry Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Performance analysis of data fusion methods applied to epileptic seizure recognition
Autorzy:
Ludwig, Simone A.
Powiązania:
https://bibliotekanauki.pl/articles/2147119.pdf
Data publikacji:
2022
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
epilepsy
ensemble method
Choquet fuzzy integral fusion
Opis:
Epilepsy is a chronic neurological disorder that is caused by unprovoked recurrent seizures. The most commonly used tool for the diagnosis of epilepsy is the electroencephalogram (EEG) whereby the electrical activity of the brain is measured. In order to prevent potential risks, the patients have to be monitored as to detect an epileptic episode early on and to provide prevention measures. Many different research studies have used a combination of time and frequency features for the automatic recognition of epileptic seizures. In this paper, two fusion methods are compared. The first is based on an ensemble method and the second uses the Choquet fuzzy integral method. In particular, three different machine learning approaches namely RNN, ML and DNN are used as inputs for the ensemble method and the Choquet fuzzy integral fusion method. Evaluation measures such as confusion matrix, AUC and accuracy are compared as well as MSE and RMSE are provided. The results show that the Choquet fuzzy integral fusion method outperforms the ensemble method as well as other state-of-the-art classification methods.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 1; 5--17
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Use of Fuzzy Evaluation and Radical Cut-Off Strategy to Improve Apictorial Puzzle Assembly with Exhaustive Search Algorithm Performance
Autorzy:
Skulimowski, Stanisław
Montusiewicz, Jerzy
Badurowicz, Marcin
Powiązania:
https://bibliotekanauki.pl/articles/2180605.pdf
Data publikacji:
2022
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
fuzzy logic
exhaustive search
reassembling
linguistic methods
puzzle
contour description
fail-fast design
cut-off strategy
Opis:
The paper presents an approach to solving the problem of assembling broken, flat elements using a letter notation of the elements’ contours and checking their matching using linguistic methods. Previous studies with the use of exhaustive search have shown effectiveness in finding possible connections, but they are burdened with a large number of calculations and the time needed to carry them out. In order to accelerate the process of searching for solutions, the possibility of using a fail-fast method of fuzzy assessment of potential combinations of elements was checked, as well as the method of cutting off potential, but not effective connections. The numerical experiment carried out showed a significant reduction in the number of trials and total computation time while maintaining the quality of the potential solutions found.
Źródło:
Advances in Science and Technology. Research Journal; 2022, 16, 2; 179--187
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An intuitionistic fuzzy extension of the codas-sort method
Autorzy:
Ouhibi, Abir
Moalla Frikha, Hela
Powiązania:
https://bibliotekanauki.pl/articles/2027996.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
CODAS-SORT
Intuitionistic fuzzy set
Multicriteria decision aid
Sorting methods
Opis:
Currently, an important issue in multi-criteria decision-making (MCDM) problems are vagueness and lack of precision of decision-making information because of insufficient data and incapability of the decision maker to process the information. Intuitionistic fuzzy sets (IFS) are a solution to eliminate the vagueness and the uncertainty. While fuzzy sets (FS) deal with ambiguity and vagueness problem, IFSs have more advantages. Moreover, the CODAS-SORT method cannot handle the uncertainty and ambiguity of information provided by human judgments. The aim of this study is to develop an IF extension of CODAS-SORT combining this method with the IFS theory. To achieve this, we use the fuzzy weighted Euclidean distance and fuzzy weighted Hamming distance instead of the crisp distances. A case study of a supplier selection assessment is used to clarify the details of our proposed method.
Źródło:
Multiple Criteria Decision Making; 2021, 16; 110-121
2084-1531
Pojawia się w:
Multiple Criteria Decision Making
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Applicability of Fuzzy and Fuzzy Analytic Hierarchy Process (Fuzzy AHP) Methods to Determine the Optimum Soil Depth in Land Suitability Evaluation for Irrigated Rice
Autorzy:
Mahabadi, Nafiseh Yaghmaeian
Mahmoud Soltani, Shahram
Powiązania:
https://bibliotekanauki.pl/articles/2088177.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:
multi-criteria land evaluation
fuzzy set theory
rice
yield
Opis:
The conventional Boolean logic models of land suitability assessment disregard the continuity concepts of the soil and landscape which might cause inaccurate evaluation and classification. To overcome this uncertainty and consequent constraints, the fuzzy set theories were introduced. Therefore, the current study was undertaken to estimate the optimum soil depth that is used in land suitability evaluation for irrigated rice through the fuzzy sets theory and analytic hierarchy process (fuzzy AHP) in Guilan Province, Iran. The square root and quantitative land suitability evaluation methods were employed to calculate traditional land suitability indices (for depths, 0-25, 0-50, 0-75, and 0-100 cm). Also, fuzzy and fuzzy AHP methods were used to explore new land indices. The Sarma similarity indices were used to compare the results of traditional and fuzzy methods for different soil depths. The results showed that the compatibility percentage between the representative pedons (0-100 cm) and the findings of this research (0-50 and 0-75 cm) were remarkable. Furthermore, the highest compatibility percentage of land suitability class was related to the comparison of these two former depths and 0 to 100 cm depths in each of the two used fuzzy methods. Besides, except for 0-25 cm depths, actual yield revealed a significant and positive correlation with the rest three soil pedon depths. These findings show that considering 0 to 50 cm soil depth might be a relevant alternative as the optimal depth to evaluate land suitability for rice in paddy fields in the Guilan rice-growing area. 
Źródło:
Polish Journal of Soil Science; 2021, 54, 1; 103-122
0079-2985
Pojawia się w:
Polish Journal of Soil Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparison of Intelligent Control Methods for the Ore Jigging Process
Autorzy:
Kulakova, Yelena
Wójcik, Waldemar
Suleimenov, Batyrbek
Smolarz, Andrzej
Powiązania:
https://bibliotekanauki.pl/articles/1844513.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
neural network
ore jiggling
control algorithm
fuzzy logic
correlation
Opis:
Efficient control of the process of jigging ore of small and fine grain allows avoiding the loss of valuable material in production residual. Due to the multi-dimensionality and multi-connectivity of this enrichment process, classical control methods do not allow achieving the maximum technological indicators of enrichment. This paper proposes investigating intelligent algorithms for controlling the jigging process, which determine the key variables - the level of the natural «bed» and the ripple frequency of the jigging machine. Algorithms are developed using fuzzy logic, neural and hybrid networks. The adequacy of intelligent algorithms was evaluated using the following criteria: correlation of expert and model values (R); Root Mean Square Error (RMSE); Mean absolute percentage error (MAPE). To assess the adequacy of the obtained algorithms, a test sample of input variables, different from the training one, was compiled. As a consequence, we determined an algorithm that gives a minimal discrepancy between the calculated and experimental data.
Źródło:
International Journal of Electronics and Telecommunications; 2021, 67, 3; 529-534
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Visual methods of processing survey data in social disciplines based on fuzzy logic
Autorzy:
Śmigielski, Grzegorz
Mreła, Aleksandra
Sokolov, Oleksandr
Nedashkovskyy, Mykoła
Powiązania:
https://bibliotekanauki.pl/articles/2086872.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
information system
quality of education
fuzzy relations
optimistic fuzzy aggregation norm
system informacyjny
jakość edukacji
relacje rozmyte
optymistyczna rozmyta norma agregacji
Opis:
All universities are responsible for assessing the quality of education. One of the required factors is the results of the students’ research. The procedure involves, most often, the preparation of the questionnaire by the staff, which is voluntarily answered by students; then, the university staff uses the statistical methods to analyze data and prepare reports. The proposed EQE method by the application of the fuzzy relations and the optimistic fuzzy aggregation norm may show a closer connection between the students’ answers and the achieved results. Moreover, the objects obtained by the application of the EQE method can be visualized by using the t-SNE technique, cosine between vectors and distances of points in five-dimensional space.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 5; e138812, 1--8
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new auto adaptive fuzzy hybrid particle swarm optimization and genetic algorithm
Autorzy:
Dziwiński, Piotr
Bartczuk, Łukasz
Paszkowski, Józef
Powiązania:
https://bibliotekanauki.pl/articles/1837533.pdf
Data publikacji:
2020
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
hybrid methods
Particle Swarm Optimization
Genetic Algorithm
fuzzy systems
multimodal function
Opis:
The social learning mechanism used in the Particle Swarm Optimization algorithm allows this method to converge quickly. However, it can lead to catching the swarm in the local optimum. The solution to this issue may be the use of genetic operators whose random nature allows them to leave this point. The degree of use of these operators can be controlled using a neuro-fuzzy system. Previous studies have shown that the form of fuzzy rules should be adapted to the fitness landscape of the problem. This may suggest that in the case of complex optimization problems, the use of different systems at different stages of the algorithm will allow to achieve better results. In this paper, we introduce an auto adaptation mechanism that allows to change the form of fuzzy rules when solving the optimization problem. The proposed mechanism has been tested on benchmark functions widely adapted in the literature. The results verify the effectiveness and efficiency of this solution.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 2; 95-111
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
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:
The extention rank ordering criteria weighting methods in fuzzy enviroment
Autorzy:
Roszkowska, Ewa
Powiązania:
https://bibliotekanauki.pl/articles/406326.pdf
Data publikacji:
2020
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
multi-criteria decision analysis
criteria weights
criteria ranking
fuzzy criteria ranking
fuzzy criteria weights
Opis:
Weight elicitation is an important part of multi-criteria decision analysis. In real-life decisionmaking problems precise information is seldom available, and providing weights is often cognitively demanding as well as very time- and effort-consuming. The judgment of decision-makers (DMs) depends on their knowledge, skills, experience, personality, and available information. One of the weights determination approaches is ranking the criteria and converting the resulting ranking into numerical values. The best known and most widely used are rank sum, rank reciprocal and centroid weights techniques. The goal of this paper is to extend rank ordering criteria weighting methods for imprecise data, especially fuzzy data. Since human judgments, including preferences, are often vague and cannot be expressed by exact numerical values, the application of fuzzy concepts in elicitation weights is deemed relevant. The methods built on the ideas of rank order techniques take into account imprecise information about rank. The fuzzy rank sum, fuzzy rank reciprocal, and fuzzy centroid weights techniques are proposed. The weights obtained for each criterion are triangular fuzzy numbers. The proposed fuzzy rank ordering criteria weighting methods can be easily implemented into decision support systems. Numerical examples are provided to illustrate the practicality and validity of the proposed methods.
Źródło:
Operations Research and Decisions; 2020, 30, 2; 91-114
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sensitivity analysis of fuzzy-analytic hierarchical process (FAHP) decision-making model in selection of underground metal mining method
Autorzy:
Balusa, Bhanu Chander
Gorai, Amit Kumar
Powiązania:
https://bibliotekanauki.pl/articles/91925.pdf
Data publikacji:
2019
Wydawca:
Główny Instytut Górnictwa
Tematy:
decision-making
mining methods
fuzzy AHP
sensitivity analysis
podejmowanie decyzji
metody wydobycia
rozmyty analityczny proces hierarchiczny
analiza wrażliwości
Opis:
This study aims to analyse the sensitivity in decision-making which results in the selection of the appropriate underground metal mining method using the fuzzy-analytical hierarchy process (FAHP) model. The proposed model considers sixteen criteria for the selection of the most appropriate mining method out of the seven. The model consists of three-layer viz. the first layer represents the criteria (factors which influence the mining method), the second layer represents the sub-criteria (categorisation of the factors) and the third layer represents the alternatives (mining methods). The priority of the different mining methods was determined based on global weights. The global weights of seven mining method were determined using a different fuzzification factor under different decision-making attitudes (optimistic, pessimistic and unbiased). The sensitivity of the decision-making results was analysed in order to understand the robustness of the model.
Źródło:
Journal of Sustainable Mining; 2019, 18, 1; 8-17
2300-1364
2300-3960
Pojawia się w:
Journal of Sustainable Mining
Dostawca treści:
Biblioteka Nauki
Artykuł

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