Search results for "Continuous"

showing 10 items of 899 documents

Enhanced quantification of wollastonite and calcite in limestone using fluorescence correction based on continuous wavelet transformation for Raman

2020

Raman spectroscopy offers a nondestructive means to identify minerals in rocks, but the ability to use the technology for quantitative mineralogical analysis is limited by fluorescence that can mask the spectral features of minerals. In this paper we apply continuous wavelet transformation (CWT) to remove fluoresence from Raman data acquired from 26 carbonate rock samples. We then record the intensity values of individual spectral features, proxies for mineral abundances, using the original Raman data and the thus inferred CWT data. The intensity values are then compared against the known mineral abundances determined using the scanning electron microscope (SEM) technology. This comparison …

Materials sciencespektroskopiaMineralogy02 engineering and technologyengineering.materialwavelets01 natural sciencesWollastonitewollastonitesymbols.namesakechemistry.chemical_compoundWaveletContinuous waveletmineraalitmineralogiaRamanInstrumentationSpectroscopyCalcite010401 analytical chemistryfluoresenssi021001 nanoscience & nanotechnologyFluorescence0104 chemical sciencesTransformation (function)chemistrysymbolsengineeringfluorescence0210 nano-technologyRaman spectroscopycalciteApplied Spectroscopy Reviews
researchProduct

A genetic algorithm for the minimum generating set problem

2016

Graphical abstractDisplay Omitted HighlightsWe propose a novel formulation for the MGS problem based on multiple knapsack.The so-conceived MGS problem is solved by a novel GA.The GA embeds an intelligent construction method and specialized crossover operators.We perform a thorough comparison with regards to state-of-the-art algorithms.The proposal proves to be very competitive, specially for large and hard instances. Given a set of positive integers S, the minimum generating set problem consists in finding a set of positive integers T with a minimum cardinality such that every element of S can be expressed as the sum of a subset of elements in T. It constitutes a natural problem in combinat…

Mathematical optimization021103 operations researchContinuous knapsack problemCrossover0211 other engineering and technologies02 engineering and technologyCutting stock problemKnapsack problemGenetic algorithm0202 electrical engineering electronic engineering information engineeringSubset sum problem020201 artificial intelligence & image processingGreedy algorithmSoftwareGeneralized assignment problemMathematicsApplied Soft Computing
researchProduct

TCSC allocation based on line flow based equations via mixed-integer programming

2007

Summary form only given. Research effort has been given to locate the optimal locations of thyristor-controlled series capacitor (TCSC) and their initial compensation levels using mixed-integer programming (MIP). As a useful technique for combinatorial optimisation over integer and continuous variables, the MIP approach can provide robust performance as well as high computational efficiency while solving complex optimal problems. Previous work using MIP employed DC load flow model ignoring reactive power balance, power loss and transformer tap ratios. In this paper, a new planning method is developed based on recently reported line flow equations and basic linearisation of binary-continuous…

Mathematical optimizationEngineeringLinear programmingLine flowbusiness.industryEnergy Engineering and Power TechnologyThyristorAC powerlaw.inventionContinuous variableElectric power systemCapacitorFlexible AC transmission systemControl theorylawQuadratic programmingElectrical and Electronic EngineeringTransformerbusinessInteger programmingVoltage2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century
researchProduct

Achieving Fair Load Balancing by Invoking a Learning Automata-Based Two-Time-Scale Separation Paradigm.

2020

Author's accepted manuscript. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. In this article, we consider the problem of load balancing (LB), but, unlike the approaches that have been proposed earlier, we attempt to resolve the problem in a fair manner (or rather, it would probably be more appropriate to describe it as an ε-fair manner because, although the LB…

Mathematical optimizationLearning automataComputer Networks and Communicationsbusiness.industryStochastic processComputer scienceQuality of serviceResource allocationsCloud computingLoad balancing (computing)Continuous learning automatonsComputer Science ApplicationsArtificial IntelligenceServerResource allocationFair load balancingbusinessVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550SoftwareIEEE transactions on neural networks and learning systems
researchProduct

Robust control of uncertain multi-inventory systems via linear matrix inequality

2008

We consider a continuous time linear multi inventory system with unknown demands bounded within ellipsoids and controls bounded within ellipsoids or polytopes. We address the problem of "-stabilizing the inventory since this implies some reduction of the inventory costs. The main results are certain conditions under which "-stabilizability is possible through a saturated linear state feedback control. All the results are based on a Linear Matrix Inequalities (LMIs) approach and on some recent techniques for the modeling and analysis of polytopic systems with saturations.

Mathematical optimizationLinear Matrix InequalitiesPolytopeDynamical Systems (math.DS)stock control93xxcontinuous systems linear matrix inequalities linear systems manufacturing systems robust control state feedback stock control uncertain systemsimpulse control inventory control hybrid systemsSettore ING-INF/04 - AutomaticaControl theoryFOS: Mathematicsmanufacturing systemsMathematics - Dynamical Systemslinear matrix inequalitiesstate feedbackTime complexityMathematics - Optimization and ControlInventory systemsMathematicsInventory controlLinear Matrix Inequalities; Inventory systemsLinear systemlinear systemsLinear matrix inequality93Cxx;93xxLinearity93Cxxhybrid systemsEllipsoidComputer Science Applicationsimpulse control; inventory control; hybrid systemsuncertain systemsControl and Systems EngineeringOptimization and Control (math.OC)Control systemBounded functioncontinuous systemsPerpetual inventorycontinuous systems; linear matrix inequalities; linear systems; manufacturing systems; robust control; state feedback; stock control; uncertain systemsinventory controlRobust controlSettore MAT/09 - Ricerca Operativarobust controlimpulse control
researchProduct

Greedy versus Dynamic Channel Aggregation Strategy in CRNs: Markov Models and Performance Evaluation

2011

Part 1: - PE-CRN 2011 Workshop; International audience; In cognitive radio networks, channel aggregation techniques which aggregate several channels together as one channel have been proposed in many MAC protocols. In this paper, we consider elastic data traffic and spectrum adaptation for channel aggregation, and propose two new strategies named as Greedy and Dynamic respectively. The performance of channel aggregation represented by these strategies is evaluated using continuous time Markov chain models. Moreover, simulation results based on various traffic distributions are utilized in order to evaluate the validity and preciseness of the mathematical models.

Mathematical optimizationMathematical modelComputer science020209 energycontinuous time Markov chain modelsAggregate (data warehouse)Cognitive radio networks020206 networking & telecommunications02 engineering and technologyMarkov modelchannel aggregation strategyperformance evaluationContinuous-time Markov chain[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]Cognitive radio0202 electrical engineering electronic engineering information engineeringDynamic channel[INFO]Computer Science [cs]SimulationComputer Science::Information TheoryCommunication channel
researchProduct

Discrete-timeH −  ∕ H ∞ sensor fault detection observer design for nonlinear systems with parameter uncertainty

2013

SUMMARY This work concerns robust sensor fault detection observer (SFDO) design for uncertain and disturbed discrete-time Takagi–Sugeno (T–S) systems using H −  ∕ H ∞ criterion. The principle of the proposed approach is based on simultaneously minimizing the perturbation effect and maximizing the fault effect on the residual vector. Furthermore, by introducing slack decision matrices and taking advantage of the descriptor formulation, less conservative sufficient conditions are proposed leading to easier linear matrix inequalities (LMIs). Moreover, the proposed (SFDO) design conditions allow dealing with unmeasurable premise variables. Finally, a numerical example and a truck–trailer system…

Mathematical optimizationMechanical EngineeringGeneral Chemical EngineeringBiomedical EngineeringAerospace EngineeringPerturbation (astronomy)ResidualIndustrial and Manufacturing EngineeringFault detection observerSystem modelNonlinear systemDiscrete time and continuous timeControl and Systems EngineeringControl theoryDecision matrixElectrical and Electronic EngineeringDesign methodsMathematicsInternational Journal of Robust and Nonlinear Control
researchProduct

Learning Automata-Based Solutions to Stochastic Nonlinear Resource Allocation Problems

2009

“Computational Intelligence” is an extremely wide-ranging and all-encompassing area. However, it is fair to say that the strength of a system that possesses “Computational Intelligence” can be quantified by its ability to solve problems that are intrinsically hard. One such class of NP-Hard problems concerns the so-called family of Knapsack Problems, and in this Chapter, we shall explain how a sub-field of Artificial Intelligence, namely that which involves “Learning Automata”, can be used to produce fast and accurate solutions to “difficult” and randomized versions of the Knapsack problem (KP).

Mathematical optimizationNonlinear systemClass (computer programming)Learning automataKnapsack problemContinuous knapsack problemResource allocationStochastic optimizationComputational intelligenceMathematics
researchProduct

A Highly Flexible Trajectory Model Based on the Primitives of Brownian Fields—Part II: Analysis of the Statistical Properties

2016

In the first part of our paper, we have proposed a highly flexible trajectory model based on the primitives of Brownian fields (BFs). In this second part, we study the statistical properties of that trajectory model in depth. These properties include the autocorrelation function (ACF), mean, and the variance of the path along each axis. We also derive the distribution of the angle-of-motion (AOM) process, the incremental traveling length process, and the overall traveling length. It is shown that the path process is in general non-stationary. We show that the AOM and the incremental traveling length processes can be modeled by the phase and the envelope of a complex Gaussian process with no…

Mathematical optimizationUniform distribution (continuous)Applied MathematicsGaussianAutocorrelationMathematical analysis020206 networking & telecommunications020302 automobile design & engineering02 engineering and technologyComputer Science ApplicationsComplex normal distributionsymbols.namesake0203 mechanical engineeringLog-normal distribution0202 electrical engineering electronic engineering information engineeringsymbolsTrajectoryElectrical and Electronic EngineeringGaussian processRandom variableMathematicsIEEE Transactions on Wireless Communications
researchProduct

Signal Restoration via a Splitting Approach

2012

International audience; In the present study, a novel signal restoration method from noisy data samples is presented and is termed as "signal split (SSplit)" approach. The new method utilizes Stein unbiased risk estimate estimator to split the signal, the Lipschitz exponents to identify noise elements and a heuristic approach for the signal reconstruction. However, unlike many noise removal techniques, the present method works only in the non-orthogonal domain. Signal restoration was performed on each individual part by finding the best compromise between the data samples and the smoothing criteria. Statistical results are quite promising and suggest better performance than the conventional…

Mathematical optimization[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processingsplit or segmentationthresholding02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingSignalmodulus maxima[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineeringLipschitz exponentMathematicscontinuous wavelet transformSignal reconstructionHeuristicNoise (signal processing)Estimator020206 networking & telecommunicationsLipschitz continuityStein unbiased risk estimatewavelet transform modulus maxima020201 artificial intelligence & image processingAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSmoothingEnergy (signal processing)
researchProduct