Search results for "NUMBER"

showing 10 items of 3939 documents

Influence of friction stir processing conditions on the manufacturing of Al-Mg-Zn-Cu alloy/boron carbide surface composite

2018

Abstract Surface metal matrix composites were synthesized via friction stir processing (FSP) on the surface of aluminium alloy 7075 (AA 7075) sheets by incorporating B4C particles (B4CP). The influence of tool rotational speeds, powder particle sizes, and change in tool travel direction between FSP passes on particle distribution and resulting properties were studied in detail. Change in tool travel direction, decreased tool rotation speed and fine B4C particles enhanced B4CP distribution and wear properties thereof. Wear resistance of composites were doubled on account of the B4CP distribution and resultant several strengthening mechanisms.

0209 industrial biotechnologyFriction stir processingMaterials scienceAlloyComposite number02 engineering and technologyBoron carbideengineering.materialIndustrial and Manufacturing EngineeringFriction stir processingchemistry.chemical_compound020901 industrial engineering & automationWearAluminium alloyAluminiumBoron carbideComposite materialSettore ING-IND/16 - Tecnologie E Sistemi Di LavorazioneStrengthening mechanisms of materialsMetals and AlloysRotational speed021001 nanoscience & nanotechnologyComputer Science ApplicationsMetal matrix compositechemistryModeling and Simulationvisual_artCeramics and Compositesvisual_art.visual_art_mediumengineeringParticleMaterials processing0210 nano-technology
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Introducing a Fuzzy-Pattern Operator in Fuzzy Time Series

2017

In this paper we introduce a fuzzy pattern operator and propose a new weighting fuzzy time series strategy for generating accurate ex-post forecasts. A decision support system is built for managing the weights of the information provided by the historical data, under a fuzzy time series framework. Our procedure analyzes the historical performance of the time series using different experiments, and it classifies the characteristics of the series through a fuzzy operator, providing a trapezoidal fuzzy number as one-step ahead forecast. We also present some numerical results related to the predictive performance of our procedure with time series of financial data sets.

0209 industrial biotechnologyFuzzy classificationSeries (mathematics)Computer science02 engineering and technologycomputer.software_genreDefuzzificationFuzzy logicWeighting020901 industrial engineering & automationFuzzy mathematics0202 electrical engineering electronic engineering information engineeringFuzzy numberFuzzy set operations020201 artificial intelligence & image processingData miningcomputer
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Fault detection for nonlinear networked systems based on quantization and dropout compensation: An interval type-2 fuzzy-model method

2016

Abstract This paper investigates the problem of filter-based fault detection for a class of nonlinear networked systems subject to parameter uncertainties in the framework of the interval type-2 (IT2) T–S fuzzy model-based approach. The Bernoulli random distribution process and logarithm quantizer are used to describe the measurement loss and signals quantization, respectively. In the framework of the IT2 T–S fuzzy model, the parameter uncertainty is handled by the membership functions with lower and upper bounds. A novel IT2 fault detection filter is designed to guarantee the residual system to be stochastically stable and satisfy the predefined H ∞ performance. It should be mentioned that…

0209 industrial biotechnologyLogarithmCognitive NeuroscienceQuantization (signal processing)02 engineering and technologyFuzzy control systemResidualFuzzy logicFault detection and isolationComputer Science ApplicationsNonlinear system020901 industrial engineering & automationArtificial IntelligenceControl theory0202 electrical engineering electronic engineering information engineeringFuzzy number020201 artificial intelligence & image processingMathematicsNeurocomputing
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George-Veeramani Fuzzy Metrics Revised

2018

In this note, we present an alternative approach to the concept of a fuzzy metric, calling it a revised fuzzy metric. In contrast to the traditional approach to the theory of fuzzy metric spaces which is based on the use of a t-norm, we proceed from a t-conorm in the definition of a revised fuzzy metric. Here, we restrict our study to the case of fuzzy metrics as they are defined by George-Veeramani, however, similar revision can be done also for some other approaches to the concept of a fuzzy metric.

0209 industrial biotechnologyLogicComputer scienceMathematics::General Mathematicst-norm02 engineering and technologyFuzzy logic<i>t</i>-norm020901 industrial engineering & automationGEORGE (programming language)0202 electrical engineering electronic engineering information engineeringt-conormMathematical PhysicsAlgebra and Number Theorybusiness.industrylcsh:MathematicsContrast (statistics)T-normlcsh:QA1-939Fuzzy metric spaceComputingMethodologies_PATTERNRECOGNITIONrestrictMetric (mathematics)<i>t</i>-conormfuzzy metric020201 artificial intelligence & image processingGeometry and TopologyArtificial intelligenceComputingMethodologies_GENERALbusinessAnalysisAxioms
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Forecasting portfolio returns using weighted fuzzy time series methods

2016

We propose using weighted fuzzy time series (FTS) methods to forecast the future performance of returns on portfolios. We model the uncertain parameters of the fuzzy portfolio selection models using a possibilistic interval-valued mean approach, and approximate the uncertain future return on a given portfolio by means of a trapezoidal fuzzy number. Introducing some modifications into the classical models of fuzzy time series, based on weighted operators, enables us to generate trapezoidal numbers as forecasts of the future performance of the portfolio returns. This fuzzy forecast makes it possible to approximate both the expected return and the risk of the investment through the value and a…

0209 industrial biotechnologyMathematical optimizationActuarial scienceSeries (mathematics)Mathematics::General MathematicsComputer scienceApplied MathematicsFuzzy set02 engineering and technologyFuzzy logicDefuzzificationTheoretical Computer Science020901 industrial engineering & automationArtificial Intelligence0202 electrical engineering electronic engineering information engineeringExpected returnPortfolioFuzzy number020201 artificial intelligence & image processingPortfolio optimizationSoftwareInternational Journal of Approximate Reasoning
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Optimal control of discrete-time interval type-2 fuzzy-model-based systems with D-stability constraint and control saturation

2016

This paper investigates the optimal control problem for discrete-time interval type-2 (IT2) fuzzy systems with pole constraints. An IT2 fuzzy controller is characterized by two predefined functions, and the membership functions and the premise rules of the IT2 fuzzy controller can be chosen freely. The pole assignment is considered, which is constrained in a presented disk region. Based on Lyapunov stability theory, sufficient conditions of asymptotic stability with an H ∞ performance are obtained for the discrete-time IT2 fuzzy model based (FMB) system. Based on the criterion, the desired IT2 state-feedback controller is designed to guarantee that the closed-loop system is asymptotically s…

0209 industrial biotechnologyMathematical optimizationAdaptive neuro fuzzy inference system02 engineering and technologyFuzzy control systemOptimal controlDefuzzificationFuzzy logic020901 industrial engineering & automationControl and Systems EngineeringControl theorySignal Processing0202 electrical engineering electronic engineering information engineeringFuzzy set operationsFuzzy number020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionElectrical and Electronic EngineeringSoftwareMathematicsSignal Processing
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An algebraic continuous time parameter estimation for a sum of sinusoidal waveform signals

2016

In this paper, a novel algebraic method is proposed to estimate amplitudes, frequencies, and phases of a biased and noisy sum of complex exponential sinusoidal signals. The resulting parameter estimates are given by original closed formulas, constructed as integrals acting as time-varying filters of the noisy measured signal. The proposed algebraic method provides faster and more robust results, compared with usual procedures. Some computer simulations illustrate the efficiency of our method. Copyright © 2016 John Wiley & Sons, Ltd.

0209 industrial biotechnologyMathematical optimizationNoise (signal processing)020206 networking & telecommunications02 engineering and technologySignalsymbols.namesake020901 industrial engineering & automationAmplitudeSine waveControl and Systems EngineeringSinusoidal waveformSignal Processing0202 electrical engineering electronic engineering information engineeringEuler's formulasymbolsApplied mathematicsDifferential algebraElectrical and Electronic EngineeringAlgebraic numberMathematicsInternational Journal of Adaptive Control and Signal Processing
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Fuzzy Modeling for Uncertain Nonlinear Systems Using Fuzzy Equations and Z-Numbers

2018

In this paper, the uncertainty property is represented by Z-number as the coefficients and variables of the fuzzy equation. This modification for the fuzzy equation is suitable for nonlinear system modeling with uncertain parameters. Here, we use fuzzy equations as the models for the uncertain nonlinear systems. The modeling of the uncertain nonlinear systems is to find the coefficients of the fuzzy equation. However, it is very difficult to obtain Z-number coefficients of the fuzzy equations.

0209 industrial biotechnologyProperty (philosophy)Mathematics::General MathematicsMathematicsofComputing_NUMERICALANALYSISComputational mathematics02 engineering and technologyFuzzy logicNonlinear system020901 industrial engineering & automationComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONZ number0202 electrical engineering electronic engineering information engineeringApplied mathematics020201 artificial intelligence & image processingComputingMethodologies_GENERALMathematics
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Darboux integrable system with a triple point and pseudo-abelian integrals

2016

We study pseudo-abelian integrals associated with polynomial perturbations of Dar-boux integrable system with a triple point. Under some assumptions we prove the local boundedness of the number of their zeros. Assuming that this is the only non-genericity, we prove that the number of zeros of the corresponding pseudo-abelian integrals is bounded uniformly for nearby Darboux integrable foliations.

0209 industrial biotechnologyPure mathematicsControl and OptimizationIntegrable systemTriple pointAbelian integrals[ MATH.MATH-DS ] Mathematics [math]/Dynamical Systems [math.DS]Darboux integrability[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS][MATH.MATH-DS] Mathematics [math]/Dynamical Systems [math.DS]Dynamical Systems (math.DS)02 engineering and technologyType (model theory)01 natural sciencesIntegrating factor020901 industrial engineering & automationFOS: MathematicsLimit Cycle0101 mathematicsAbelian groupMathematics - Dynamical Systems34C07 34C08MathematicsNumerical AnalysisAlgebra and Number Theory010102 general mathematicsMathematical analysisLimit cyclesMathematics Subject ClassificationControl and Systems EngineeringBounded functionFoliation (geology)
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Algebraic parameter estimation of a multi-sinusoidal waveform signal from noisy data

2013

International audience; In this paper, we apply an algebraic method to estimate the amplitudes, phases and frequencies of a biased and noisy sum of complex exponential sinusoidal signals. Let us stress that the obtained estimates are integrals of the noisy measured signal: these integrals act as time-varying filters. Compared to usual approaches, our algebraic method provides a more robust estimation of these parameters within a fraction of the signal's period. We provide some computer simulations to demonstrate the efficiency of our method.

0209 industrial biotechnology[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingSignalsymbols.namesake020901 industrial engineering & automation[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingControl theory[INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering[ INFO.INFO-AU ] Computer Science [cs]/Automatic Control Engineering0202 electrical engineering electronic engineering information engineeringFraction (mathematics)Algebraic numberNoisy data[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMathematicsEstimation theory020206 networking & telecommunicationsAmplitudeSinusoidal waveformEuler's formulasymbols[INFO.INFO-AU] Computer Science [cs]/Automatic Control EngineeringAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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