Search results for " Error."

showing 10 items of 1034 documents

On Equivalent Random Traffic method extension

2011

The key result of the paper is the Equivalent Random Traffic (ERT) method extension for estimation of the throughput for schemes with traffic splitting. The excellent accuracy (relative error is less than 1%) is shown in numerical example. A numerical algorithm is given — how to estimate the throughput for schemes at traffic splitting and merging. The paper also contains new Erlang-B formula algorithm for non-integer number of channels based on parabolic approximation.

Mathematical optimizationApproximation errorTelecommunication channelsNumerical analysisComputer Science::Networking and Internet ArchitectureKey (cryptography)Integrated opticsExtension (predicate logic)Throughput (business)Erlang (unit)AlgorithmMathematics2011 Baltic Congress on Future Internet and Communications
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Optimization of two-step batch processes and the method of compensation for random error

2012

This paper considers the problem of the optimal setting of controllable variables in two-step processes with quality constraints. The optimal setting minimizes the cost and satisfies quality constraints defined for the final output. The main emphasis is given to processes where it is possible to make intermediate measurements after the first processing step and to utilize these measurements before the control variables in the second step are set. Optimization based on this method of compensation for random error can yield substantially lower cost than does optimization based on a strategy where all variables are fixed before the process starts. An example of application of the method is tak…

Mathematical optimizationComputer scienceApplied Mathematicsmedia_common.quotation_subjectTwo stepEmphasis (telecommunications)Process (computing)Control variableAnalytical ChemistryCompensation (engineering)Set (abstract data type)Random errorQuality (business)media_commonJournal of Chemometrics
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Functional A Posteriori Error Estimates for Time-Periodic Parabolic Optimal Control Problems

2015

This article is devoted to the a posteriori error analysis of multiharmonic finite element approximations to distributed optimal control problems with time-periodic state equations of parabolic type. We derive a posteriori estimates of the functional type, which are easily computable and provide guaranteed upper bounds for the state and co-state errors as well as for the cost functional. These theoretical results are confirmed by several numerical tests that show high efficiency of the a posteriori error bounds. peerReviewed

Mathematical optimizationControl and OptimizationMathematicsofComputing_NUMERICALANALYSISFinite element approximations010103 numerical & computational mathematicsType (model theory)01 natural sciencesparabolic time-periodic optimal control problemsError analysisFOS: MathematicsApplied mathematicsMathematics - Numerical AnalysisNumerical testsfunctional a posteriori error estimates0101 mathematicsMathematics - Optimization and Control49N20 35Q61 65M60 65F08Mathematicsta113Time periodicta111Numerical Analysis (math.NA)State (functional analysis)Optimal controlComputer Science Applications010101 applied mathematicsOptimization and Control (math.OC)multiharmonic finite element methodsSignal ProcessingA priori and a posterioriAnalysisNumerical Functional Analysis and Optimization
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Deep Drawing Process Design: A Multi Objective Optimization Approach

2009

In sheet metal forming most of the problems are multi objective problems, generally characterized by conflicting objectives. The definition of proper parameters aimed to prevent both wrinkles and fracture is a typical example of an optimization problem in sheet metal forming characterized by conflicting goals. What is more, nowadays, a great interest would be focused on the availability of a cluster of possible optimal solutions instead of a single one, particularly in an industrial environment. Thus, the design parameters calibration, accomplishing all the objectives, is difficult and sometimes unsuccessful. In order to overcome this drawback a multi-objectives optimization procedure based…

Mathematical optimizationEngineeringOptimization problembusiness.industryMechanical EngineeringProcess designTrial and errorMulti-objective optimizationBlankMechanics of MaterialsGeneral Materials ScienceProcess windowResponse surface methodologyDeep drawingbusinessKey Engineering Materials
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On central algorithms of approximation under fuzzy information

2005

We consider the problem of approximation of an operator by information described by n real characteristics in the case when this information is fuzzy. We develop the well-known idea of an optimal error method of approximation for this case. It is a method whose error is the infimum of the errors of all methods for a given problem characterized by fuzzy numbers in this case. We generalize the concept of central algorithms, which are always optimal error algorithms and in the crisp case are useful both in practice and in theory. In order to do this we define the centre of an L-fuzzy subset of a normed space. The introduced concepts allow us to describe optimal methods of approximation for lin…

Mathematical optimizationFuzzy classificationArtificial IntelligenceLogicApproximation errorFuzzy setFuzzy set operationsFuzzy numberApproximation algorithmRound-off errorAlgorithmFuzzy logicMathematicsFuzzy Sets and Systems
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On Randomness and Structure in Euclidean TSP Instances: A Study With Heuristic Methods

2021

Prediction of the quality of the result provided by a specific solving method is an important factor when choosing how to solve a given problem. The more accurate the prediction, the more appropriate the decision on what to choose when several solving applications are available. In this article, we study the impact of the structure of a Traveling Salesman Problem instance on the quality of the solution when using two representative heuristics: the population-based Ant Colony Optimization (ACO) and the local search Lin-Kernighan (LK) algorithm. The quality of the result for a solving method is measured by the computation accuracy, which is expressed using the percent error between its soluti…

Mathematical optimizationGeneral Computer ScienceComputer scienceHeuristic (computer science)Population0211 other engineering and technologies02 engineering and technologyTravelling salesman problemAnt colony optimizationApproximation error0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceLocal search (optimization)Electrical and Electronic EngineeringeducationRandomnessLin-Kernighan methodeducation.field_of_study021103 operations researchEuclidean normHeuristicbusiness.industryAnt colony optimization algorithmstraveling salesman problemGeneral EngineeringApproximation algorithm020201 artificial intelligence & image processinglcsh:Electrical engineering. Electronics. Nuclear engineeringHeuristicsbusinesslcsh:TK1-9971IEEE Access
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Effective state estimation of stochastic systems

2003

In the present paper, for constructing the minimum risk estimators of state of stochastic systems, a new technique of invariant embedding of sample statistics in a loss function is proposed. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, an invariant embedding technique is independent of the choice of priors. It allows one to eliminate unknown parameters from the problem and to find the best invariant estimator, which has smaller risk than any of the well‐known estimators. There exists a class of control systems where observations are not …

Mathematical optimizationMinimum mean square errorMathematical statisticsEstimatorTheoretical Computer ScienceMinimum-variance unbiased estimatorEfficient estimatorBias of an estimatorControl and Systems EngineeringPrior probabilityComputer Science (miscellaneous)Applied mathematicsEngineering (miscellaneous)Social Sciences (miscellaneous)Invariant estimatorMathematicsKybernetes
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Smart load prediction analysis for distributed power network of Holiday Cabins in Norwegian rural area

2020

Abstract The Norwegian rural distributed power network is mainly designed for Holiday Cabins with limited electrical loading capacity. Load prediction analysis, within such type of network, is necessary for effective operation and to manage the increasing demand of new appliances (e. g. electric vehicles and heat pumps). In this paper, load prediction of a distributed power network (i.e. a typical Norwegian rural area power network of 125 cottages with 478 kW peak demand) is carried out using regression analysis techniques for establishing autocorrelations and correlations among weather parameters and occurrence time in the period of 2014–2018. In this study, the regression analysis for loa…

Mathematical optimizationRenewable Energy Sustainability and the EnvironmentComputer science020209 energyStrategy and Management05 social sciencesAutocorrelationDistributed powerRegression analysis02 engineering and technologyLoad profileIndustrial and Manufacturing EngineeringRandom forestAutoregressive modelPeak demand050501 criminology0202 electrical engineering electronic engineering information engineeringSymmetric mean absolute percentage error0505 lawGeneral Environmental ScienceJournal of Cleaner Production
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Approximation-Based Adaptive Fuzzy Tracking Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Time-Delay Systems

2015

This paper focuses on the problem of approximation-based adaptive fuzzy tracking control for a class of stochastic nonlinear time-delay systems with a nonstrict-feedback structure. A variable separation approach is introduced to overcome the design difficulty from the nonstrict-feedback structure. Mamdani-type fuzzy logic systems are utilized to model the unknown nonlinear functions in the process of controller design, and an adaptive fuzzy tracking controller is systematically designed by using a backstepping technique. It is shown that the proposed controller guarantees that all signals in the closed-loop system are fourth-moment semiglobally uniformly ultimately bounded, and the tracking…

Mathematical optimizationStochastic processApplied MathematicsFuzzy logicTracking errorNonlinear systemComputational Theory and MathematicsArtificial IntelligenceControl and Systems EngineeringControl theoryBacksteppingAdaptive systemBounded functionMathematicsIEEE Transactions on Fuzzy Systems
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Non Linear Image Restoration in Spatial Domain

2011

International audience; In the present work, a novel image restoration method from noisy data samples is presented. The restoration was per-formed by using some heuristic approach utilizing data samples and smoothness criteria in spatial domain. Unlike most existing techniques, this approach does not require prior modelling of either the image or noise statistics. The proposed method works in an interactive mode to find the best compromise between the data (mean square error) and the smoothing criteria. The method has been compared with the shrinkage approach, Wiener filter and Non Local Means algorithm as well. Experimental results showed that the proposed method gives better signal to noi…

Mathematical optimization[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingNoise reductionWiener filter020206 networking & telecommunications02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingNon-local meansMultiplicative noisesymbols.namesakeMean Square ErrorSignal-to-noise ratio[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingGaussian noiseSignal SmoothnessRestoration0202 electrical engineering electronic engineering information engineeringsymbols020201 artificial intelligence & image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAlgorithmSmoothingImage restorationNonlinear FilteringMathematics
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