Search results for "fuzzy equation"

showing 2 items of 2 documents

Neural network approach to solving fuzzy nonlinear equations using Z-numbers

2020

In this article, the fuzzy property is described by means of the Z-number as the coefficients and variables of the fuzzy equations. This alteration for the fuzzy equation is appropriate for system modeling with Z-number parameters. In this article, the fuzzy equation with Z-number coefficients and variables is tended to be used as the models for the uncertain systems. The modeling issue related to the uncertain system is to obtain the Z-number coefficients and variables of the fuzzy equation. Nevertheless, it is extremely hard to get the Z-number coefficients of the fuzzy equations. In this article, in order to model the uncertain nonlinear systems, a novel structure of the multilayer neura…

Property (programming)Mathematics::General MathematicsReliability (computer networking)Structure (category theory)MathematicsofComputing_NUMERICALANALYSIS02 engineering and technologyfuzzy equationFuzzy logicArtificial IntelligenceComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION0202 electrical engineering electronic engineering information engineeringApplied mathematics/dk/atira/pure/subjectarea/asjc/1700MathematicsArtificial neural networkZ numberApplied MathematicsComputingSystems modelingNonlinear systemComputational Theory and MathematicsControl and Systems EngineeringUncertain nonlinear systemmultilayer neural network020201 artificial intelligence & image processingComputingMethodologies_GENERAL/dk/atira/pure/core/subjects/computingInterpolationComputer Science(all)
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Modeling and control of uncertain nonlinear systems

2018

A survey of the methodologies associated with the modeling and control of uncertain nonlinear systems has been given due importance in this paper. The basic criteria that highlights the work is relied on the various patterns of techniques incorporated for the solutions of fuzzy equations that corresponds to fuzzy controllability subject. The solutions which are generated by these equations are considered to be the controllers. Currently, numerical techniques have come out as superior techniques in order to solve these types of problems. The implementation of neural networks technique is contributed in the complex way of dealing the appropriate coefficients and solutions of the fuzzy systems.

0209 industrial biotechnologyMathematical optimizationArtificial neural networkComputer scienceComputingUncertain systemsComputational mathematics02 engineering and technologyFuzzy control systemFuzzy logicControllabilitymodellingNonlinear system020901 industrial engineering & automationuncertain systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingfuzzy equationsnonlinear systemsControl (linguistics)control/dk/atira/pure/subjectarea/asjc/1700/dk/atira/pure/core/subjects/computingComputer Science(all)
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