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A TSK-Type-Based Self-Evolving Compensatory Interval Type-2 Fuzzy Neural Network (TSCIT2FNN) and Its Applications
2014
IEEE transactions on industrial electronics (1982. Print)
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The antecedent part of each compensatory fuzzy rule is an interval type-2 fuzzy set in the TSCIT2FNN, where compensatory-based fuzzy reasoning uses adaptive fuzzy operation of a neural fuzzy system to ...
A TSCIT2FNN uses type-2 fuzzy sets in an FNN in order to handle the uncertainties associated with information or data in the knowledge base. ...
The update parameters c i and d i are used to enhance the adaptive compensatory operator. ...
doi:10.1109/tie.2013.2248332
fatcat:n5b7gmeis5hibk3byafhx44g2m
Adaptive Control of Active Magnetic Bearing against Milling Dynamics
2016
Applied Sciences
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The efficacy of ECAMA to suppress the spindle position deviation with the aid of FMRAC has been verified as well via numerical simulations and practical metal cutting. ...
In order to ensure the superior performance of spindle position regulation, the employed models in FMRAC are all constructed by experiments. ...
After the dynamic models are built, the variation in cutting force can be numerically estimated via a fuzzy logic algorithm according to the current operation conditions and parameter settings. ...
doi:10.3390/app6020052
fatcat:cu3krdsj7rdpfev52akuhjzouu
Online Recognition of Fuzzy Time Series Patterns
2009
European Society for Fuzzy Logic and Technology
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This article deals with the recognition of recurring multivariate time series patterns modelled sample-point-wise by parametric fuzzy sets. ...
Furthermore, means are introduced to enable users of the recognition system to restrict results to certain stages of a pattern's development, e. g. for forecasting purposes, all in a consistently fuzzy ...
The resulting crisp value τ * from μ(t, τ ) points to the earliest stage of development of the pattern 4 As conjunction operator, a non-compensatory operator-such as all T -norm operators-should be chosen ...
dblp:conf/eusflat/HerbstB09
fatcat:vymkfgrhpffo5lj3tzh64f7zje
Decision Making And Fuzzy Inference: A New Linked Approach
2005
European Society for Fuzzy Logic and Technology
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Basic Notions of Fuzzy Logic A fuzzy predicate is a mapping from the universe X to the interval [0, 1]; instead of the classical set {0, 1}. ...
The formulas of Propositional Compensatory Calculus are composed functions of the operators c,d, n and i. ...
Fuzzy Sets. Inf. Control 8, 338-353. -Zimmermann, H.J (1996) : Fuzzy Set Theory and its applications, Kluwer Ac. Publishers.London. ...
dblp:conf/eusflat/EspinGL05
fatcat:leyzy4jiybev5dv755kvbpdt64
A Decision-Making Approach for Ranking Tertiary Institutions' Service Quality Using Fuzzy MCDM and Extended HiEdQUAL Model
2021
Applied Computational Intelligence and Soft Computing
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The importance weight of each performance criterion is found with Fuzzy Analytical Hierarchy Process (FAHP) algorithm. ...
Therefore, a fuzzy method was proposed to resolve the ambiguity of the concepts and intra-uncertainty, which are associated with human judgments in decision-making. ...
Acknowledgments e authors are grateful to the Covenant University for providing conducive environment and adequate support for carrying out this research work. ...
doi:10.1155/2021/4163906
doaj:0c76baf68db0478e829a4f9c6ccdee2e
fatcat:sk2v2r3yknd23kjsc2gquuo56u
Transdisciplinary Scientific Strategies for Soft Computing Development: Towards an Era of Data and Business Analytics
2021
Axioms
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The paper also shows how these strategies are expressed in three dimensions of an ambitious actions plan. ...
They are all integrated into a master strategy called wide knowledge discovery, which offers a way towards the augmented analytics paradigm. ...
general and theoretical hybridization, with a positive impact on analytics performed by fuzzy predicates. ...
doi:10.3390/axioms10020093
fatcat:uwsjhk62nnfktf6lwh4ocabwou
Hyperbox based machine learning algorithms: A comprehensive survey
[article]
2019
arXiv
pre-print
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In general, according to the architecture and characteristic features of the resulting models, the existing hyperbox-based learning algorithms may be grouped into three major categories: fuzzy min-max ...
With the rapid development of digital information, the data volume generated by humans and machines is growing exponentially. ...
The classifying part is used for computing membership values for various classes.
invented a new fuzzy min-max model based on fuzzy min-max neural network with modified compensatory neurons. ...
arXiv:1901.11303v3
fatcat:ak66d74lxvbp7j3hjg4mzvqlr4
Elicitation of criteria weights for multicriteria models: Bibliometrics, typologies, characteristics and applications
2021
Brazilian Journal of Operations & Production Management
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The MCDA has a wide application on operation and production management. ...
The main contributions are published on European Journal of Operational Research journal. ...
Fuzzy Some subjective methods employ the fuzzy set theory, or fuzzy logic, in their conception. ...
doi:10.14488/bjopm.2021.014
fatcat:qml367y5lfailcxvykoz7jri5u
Solving the over segmentation problem in applications of Watershed Transform
2013
Journal of Biomedical Graphics and Computing
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Methods: We define internal markers, by algorithms based on clustering and fuzzy logic in order to join the oversegmented regions with statistical features. ...
Results: The results show that the proposed methods self-adapt to the different image objects characteristics. An improvement of the accuracy is obtained. ...
When analyzing fuzzy operators, the compensatory logic presented a lower error in all the 47 tested images. The mean value of the error was 0.102 and the standard deviation 0.07. ...
doi:10.5430/jbgc.v3n3p29
fatcat:pix7mw4mufgqhdj546etabqj7m
Two-Strategy reinforcement group cooperation based symbiotic evolution for TSK-type fuzzy controller design
2012
Artificial intelligence research
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Each group represents a set of the chromosomes that belongs to a fuzzy rule and can cooperate with other groups to generation the better chromosomes by using elites-base compensation crossover strategy ...
This paper proposes a TSK-type fuzzy controller (TFC) with a two-strategy reinforcement group cooperation based symbiotic evolution (TSR-GCSE) for solving various control problems. ...
Karr [19] applied GAs to the design of the membership functions of a fuzzy controller, with the fuzzy rule set assigned in advance. ...
doi:10.5430/air.v1n1p1
fatcat:5uo5ici3wfanvcfa3ds2hl4lda
A Fuzzy Decision Support System for Drawing Directions from Purchasing Portfolio Models
[chapter]
2013
IFIP Advances in Information and Communication Technology
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With these aims, a fuzzy-based DSS is designed and implemented. ...
The fuzzy DSS is applied to a demonstrative case study of an American multinational company operating in the field of Electric Power Systems and Alternative Energy Systems. ...
fuzzy logic as potential useful and flexible way to deal with the measurement of variables and the item positioning, as well as to arrange a not-compensatory decision logic and support user during the ...
doi:10.1007/978-3-642-40361-3_72
fatcat:2bel5aim5neqtcwflzpmn64tru
Application of fuzzy sets to optimal reactive power planning with security constraints
1994
IEEE Transactions on Power Systems
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Voltage constraints within each area are modeled as fuzzy sets for the static security analysis by biasing the final solution towards desired values of variables within their given ranges. ...
The operation problem is decomposed into 4 subproblems via Dantzig-Wolfe decomposition (DWD), and the modeling of multi-area power systems is considered by applying a second DWD to each subproblem, leading ...
In this paper, fuzzy modeling offers a tighter control on bus voltages within their operating ranges for enhancing the system security. ...
doi:10.1109/59.317685
fatcat:dnwb222ncrdr7ahewajqkfrvzi
Application of fuzzy sets to optimal reactive power planning with security constraints
1993
Conference Proceedings Power Industry Computer Application Conference
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Voltage constraints within each area are modeled as fuzzy sets for the static security analysis by biasing the final solution towards desired values of variables within their given ranges. ...
The operation problem is decomposed into 4 subproblems via Dantzig-Wolfe decomposition (DWD), and the modeling of multi-area power systems is considered by applying a second DWD to each subproblem, leading ...
In this paper, fuzzy modeling offers a tighter control on bus voltages within their operating ranges for enhancing the system security. ...
doi:10.1109/pica.1993.291026
fatcat:owo45pd3mnhj7nkmw5fgodycde
An Efficient Camera Identification Technique using Krawtchouk Moment Invariants
2019
JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES
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These invariants are fed to Fuzzy Min-Max Neural Network with Compensatory Neuron (FMCN) and by performing ten-fold cross-validation technique, verification is made out. ...
At the point when this happens, a falsifier or attacker can effortlessly operate digital content, for example, pictures or video to make perceptually reasonable frauds [XI]. ...
Classification To represent the pattern classes hyperbox fuzzy sets used by the Fuzzy Min-Max Neural Network with Compensatory Neuron (FMCN) [IV] . ...
doi:10.26782/jmcms.2019.02.00004
fatcat:xql6xhin6bfgfhowr3qjoqncau
Fuzzy Control Strategies in Human Operator and Sport Modeling
[article]
2009
arXiv
pre-print
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The motivation behind mathematically modeling the human operator is to help explain the response characteristics of the complex dynamical system including the human manual controller. ...
In this paper, we present two different fuzzy logic strategies for human operator and sport modeling: fixed fuzzy-logic inference control and adaptive fuzzy-logic control, including neuro-fuzzy-fractal ...
Significant success has been achieved in modeling human operators performing compensatory and pursuit tracking tasks by employing continuous, quasi-linear operator models. ...
arXiv:0907.1212v1
fatcat:wfjnuxnf3rgnbenz7kay453mve
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