Search results for "learning theory"

showing 10 items of 216 documents

Supporting group decision makers to locate temporary relief distribution centres after sudden-onset disasters

2020

International audience; In the humanitarian response, multiple decision-makers (DMs) need to collaborate in various problems, such as locating temporary relief distribution centres (RDCs). Several studies have argued that maximising demand coverage, reducing logistics costs and minimising response time are among the critical objectives when locating RDCs after a sudden-onset disaster. However, these objectives are often conflicting and the trade-offs can considerably complicate the situation for finding a consensus.To address the challenge and support the DMs, we suggest investigating the stability of non-dominated alternatives derived from a multi-objective model based on Monte Carlo Simul…

010504 meteorology & atmospheric sciencesComputer sciencemedicine.medical_treatment0211 other engineering and technologiesStability (learning theory)Distribution (economics)02 engineering and technology01 natural sciencesHumanitarian responseNATURAL DISASTERSupport groupINFORMATION-MANAGEMENT[SPI]Engineering Sciences [physics]NETWORK DESIGNGroup decision-making2015 Nepal earthquakemedicineOPTIMIZATIONVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Monte Carlo simulation0105 earth and related environmental sciences021110 strategic defence & security studiesCOORDINATIONCOMPLEXDISTRIBUTION MODELbusiness.industrySTOCHASTIC-MODELHumanitarian responseGeologyGeotechnical Engineering and Engineering GeologyRisk analysis (engineering)Multiobjective facility locationPARETO SETbusinessSafety ResearchHUMANITARIAN LOGISTICSSudden onsetInternational Journal of Disaster Risk Reduction
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The ecogenetic link between demography and evolution: can we bridge the gap between theory and data?

2007

Calls to understand the links between ecology and evolution have been common for decades. Population dynamics, i.e. the demographic changes in populations, arise from life history decisions of individuals and thus are a product of selection, and selection, on the contrary, can be modified by such dynamical properties of the population as density and stability. It follows that generating predictions and testing them correctly requires considering this ecogenetic feedback loop whenever traits have demographic consequences, mediated via density dependence (or frequency dependence). This is not an easy challenge, and arguably theory has advanced at a greater pace than empirical research. Howeve…

0106 biological sciences*Ecosystemcomparative analysisdensity-dependent selectionEcology (disciplines)Frequency-dependent selectionPopulationPopulation DynamicsStability (learning theory)Biologylife history theory010603 evolutionary biology01 natural sciencesecogeneticsLife history theory03 medical and health sciencesEmpirical researchAnimalsexperimental evolutionSelection GeneticeducationEcology Evolution Behavior and SystematicsSelection (genetic algorithm)Ecosystem030304 developmental biology0303 health scienceseducation.field_of_studyEcologyEcologyBiological Evolutioneco-evolutionary feedback*Evolution*Selection (Genetics)frequency-dependent selectionEcology/*methodsEvolutionary ecologyEcology letters
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Effects of multiple stressors on the dimensionality of ecological stability

2021

Abstract Ecological stability is a multidimensional construct. Investigating multiple stability dimensions is key to understand how ecosystems respond to disturbance. Here, we evaluated the single and combined effects of common agricultural stressors (insecticide, herbicide and nutrients) on four dimensions of stability (resistance, resilience, recovery and invariability) and on the overall dimensionality of stability (DS) using the results of a freshwater mesocosm experiment. Functional recovery and resilience to pesticides were enhanced in nutrient‐enriched systems, whereas compositional recovery was generally not achieved. Pesticides did not affect compositional DS, whereas functional DS…

0106 biological sciencesLettermedia_common.quotation_subjectStability (learning theory)Fresh Waterfunctional ecology010603 evolutionary biology01 natural sciencesMesocosmrecoveryEcosystemLettersPesticidescommunity compositionresilienceEcosystemEcology Evolution Behavior and Systematicsmedia_commondisturbanceEcological stabilityFunctional ecologyResistance (ecology)HerbicidesEcology010604 marine biology & hydrobiologyQ Science (General)Agriculture15. Life on landpopulationsmultiple stressorsmesocosm experimentDisturbance (ecology)ecological stabilityEnvironmental sciencePsychological resiliencecommunity ecologyEcology Letters
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Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing Algorithm

2019

International audience; This paper deals with motion control for an 8-degree-of-freedom (DOF) high performance driving simulator. We formulate a constrained optimal control that defines the dynamical behavior of the system. Furthermore, the paper brings together various methodologies for addressing feasibility issues arising in implicit model predictive control-based motion cueing algorithms.The implementation of different techniques is described and discussed subsequently. Several simulations are carried out in the simulator platform. It is observed that the only technique that can provide ensured closed-loop stability by assuring feasibility over all prediction horizons is a braking law t…

0209 industrial biotechnology021103 operations researchComputer scienceDriving simulationControl (management)0211 other engineering and technologiesStability (learning theory)Driving simulator02 engineering and technologyModélisation et simulation [Informatique]Motion controlOptimal control[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationAutomatique / Robotique [Sciences de l'ingénieur]Motion (physics)[SPI.AUTO]Engineering Sciences [physics]/AutomaticModel predictive controlAcceleration020901 industrial engineering & automationMotion Cueing AlgorithmAlgorithmModel Predictive Control
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A class of third order iterative Kurchatov–Steffensen (derivative free) methods for solving nonlinear equations

2019

Abstract In this paper we show a strategy to devise third order iterative methods based on classic second order ones such as Steffensen’s and Kurchatov’s. These methods do not require the evaluation of derivatives, as opposed to Newton or other well known third order methods such as Halley or Chebyshev. Some theoretical results on convergence will be stated, and illustrated through examples. These methods are useful when the functions are not regular or the evaluation of their derivatives is costly. Furthermore, special features as stability, laterality (asymmetry) and other properties can be addressed by choosing adequate nodes in the design of the methods.

0209 industrial biotechnologyClass (set theory)Computer scienceIterative methodApplied MathematicsStability (learning theory)020206 networking & telecommunications02 engineering and technologyChebyshev filterComputational MathematicsNonlinear systemThird order020901 industrial engineering & automationRate of convergenceConvergence (routing)0202 electrical engineering electronic engineering information engineeringApplied mathematicsApplied Mathematics and Computation
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Finite-time stability and stabilisation for a class of nonlinear systems with time-varying delay

2014

This paper is concerned with the problems of finite-time stability FTS and finite-time stabilisation for a class of nonlinear systems with time-varying delay, which can be represented by Takagi–Sugeno fuzzy system. Some new delay-dependent FTS conditions are provided and applied to the design problem of finite-time fuzzy controllers. First, based on an integral inequality and a fuzzy Lyapunov–Krasovskii functional, a delay-dependent FTS criterion is proposed for open-loop fuzzy system by introducing some free fuzzy weighting matrices, which are less conservative than other existing ones. Then, the parallel distributed compensation controller is designed to ensure FTS of the time-delay fuzzy…

0209 industrial biotechnologyEngineeringfinite-time stabilisation; finite-time stability; fuzzy control; nonlinear system; time-delay system; Control and Systems Engineering; Theoretical Computer Science; Computer Science Applications1707 Computer Vision and Pattern RecognitionStability (learning theory)fuzzy controltime-delay system02 engineering and technologynonlinear systemFuzzy logicCompensation (engineering)Theoretical Computer Science020901 industrial engineering & automationControl theory0202 electrical engineering electronic engineering information engineeringfinite-time stabilisationfinite-time stabilityAdaptive neuro fuzzy inference systembusiness.industryComputer Science Applications1707 Computer Vision and Pattern RecognitionFuzzy control systemComputer Science ApplicationsWeightingNonlinear systemControl and Systems Engineering020201 artificial intelligence & image processingbusiness
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Online fitted policy iteration based on extreme learning machines

2016

Reinforcement learning (RL) is a learning paradigm that can be useful in a wide variety of real-world applications. However, its applicability to complex problems remains problematic due to different causes. Particularly important among these are the high quantity of data required by the agent to learn useful policies and the poor scalability to high-dimensional problems due to the use of local approximators. This paper presents a novel RL algorithm, called online fitted policy iteration (OFPI), that steps forward in both directions. OFPI is based on a semi-batch scheme that increases the convergence speed by reusing data and enables the use of global approximators by reformulating the valu…

0209 industrial biotechnologyInformation Systems and ManagementRadial basis function networkArtificial neural networkComputer sciencebusiness.industryStability (learning theory)02 engineering and technologyMachine learningcomputer.software_genreManagement Information Systems020901 industrial engineering & automationArtificial IntelligenceBellman equation0202 electrical engineering electronic engineering information engineeringBenchmark (computing)Reinforcement learning020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerSoftwareExtreme learning machineKnowledge-Based Systems
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Game Theoretic Decentralized Feedback Controls in Markov Jump Processes

2017

This paper studies a decentralized routing problem over a network, using the paradigm of mean-field games with large number of players. Building on a state-space extension technique, we turn the problem into an optimal control one for each single player. The main contribution is an explicit expression of the optimal decentralized control which guarantees the convergence both to local and to global equilibrium points. Furthermore, we study the stability of the system also in the presence of a delay which we model using an hysteresis operator. As a result of the hysteresis, we prove existence of multiple equilibrium points and analyze convergence conditions. The stability of the system is ill…

0209 industrial biotechnologyMathematical optimizationDecentralized routing policies; Hysteresis; Inverse control problem; Mean-field games; Optimal control; Control and Optimization; Management Science and Operations Research; Applied MathematicsControl and OptimizationStability (learning theory)02 engineering and technologyManagement Science and Operations ResearchMean-field games01 natural sciencesDecentralized routing policie020901 industrial engineering & automationControl theorySettore MAT/05 - Analisi MatematicaMean-field gameConvergence (routing)0101 mathematicsMean field gamesMathematicsEquilibrium pointSettore SECS-S/06 - Metodi mat. dell'economia e Scienze Attuariali e FinanziarieDecentralized routing policies; Hysteresis; Inverse control problem; Mean-field games; Optimal controlApplied MathematicsHysteresis010102 general mathematics[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]Optimal controlOptimal control Mean-field games Inverse control problem Decentralized routing policies HysteresisDecentralised systemOptimal control Mean-field games Inverse control problem Decentralized routing policies HysteresisExpression (mathematics)Optimal controlTheory of computationDecentralized routing policiesHysteresiInverse control problemRouting (electronic design automation)Settore MAT/09 - Ricerca Operativa
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New results on stability analysis and stabilization of time-delay continuous Markovian jump systems with partially known rates matrix

2015

Summary In this note, the problems of stability analysis and controller synthesis of Markovian jump systems with time-varying delay and partially known transition rates are investigated via an input–output approach. First, the system under consideration is transformed into an interconnected system, and new results on stochastic scaled small-gain condition for stochastic interconnected systems are established, which are crucial for the problems considered in this paper. Based on the system transformation and the stochastic scaled small-gain theorem, stochastic stability of the original system is examined via the stochastic version of the bounded realness of the transformed forward system. Th…

0209 industrial biotechnologyStochastic stabilityMechanical EngineeringGeneral Chemical EngineeringBiomedical EngineeringRegular polygonStability (learning theory)Aerospace Engineering02 engineering and technologyIndustrial and Manufacturing EngineeringMarkovian jumpMatrix (mathematics)020901 industrial engineering & automationControl and Systems EngineeringSystem transformationControl theoryBounded function0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingElectrical and Electronic EngineeringMathematicsInternational Journal of Robust and Nonlinear Control
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Adjusted bat algorithm for tuning of support vector machine parameters

2016

Support vector machines are powerful and often used technique of supervised learning applied to classification. Quality of the constructed classifier can be improved by appropriate selection of the learning parameters. These parameters are often tuned using grid search with relatively large step. This optimization process can be done computationally more efficiently and more precisely using stochastic search metaheuristics. In this paper we propose adjusted bat algorithm for support vector machines parameter optimization and show that compared to the grid search it leads to a better classifier. We tested our approach on standard set of benchmark data sets from UCI machine learning repositor…

0209 industrial biotechnologyWake-sleep algorithmActive learning (machine learning)Computer scienceStability (learning theory)Linear classifier02 engineering and technologySemi-supervised learningcomputer.software_genreCross-validationRelevance vector machineKernel (linear algebra)020901 industrial engineering & automationLeast squares support vector machine0202 electrical engineering electronic engineering information engineeringMetaheuristicBat algorithmStructured support vector machinebusiness.industrySupervised learningOnline machine learningParticle swarm optimizationPattern recognitionPerceptronGeneralization errorSupport vector machineKernel methodComputational learning theoryMargin classifierHyperparameter optimization020201 artificial intelligence & image processingData miningArtificial intelligenceHyper-heuristicbusinesscomputer2016 IEEE Congress on Evolutionary Computation (CEC)
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