Search results for "Emulator"

showing 10 items of 16 documents

Automatic emulator and optimized look-up table generation for radiative transfer models

2017

This paper introduces an automatic methodology to construct emulators for costly radiative transfer models (RTMs). The proposed method is sequential and adaptive, and it is based on the notion of the acquisition function by which instead of optimizing the unknown RTM underlying function we propose to achieve accurate approximations. The Automatic Gaussian Process Emulator (AGAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the good capabilities of the method in toy examples and for the construction of an…

010504 meteorology & atmospheric sciencesComputer scienceFlatness (systems theory)0211 other engineering and technologiesAtmospheric correctionSampling (statistics)02 engineering and technologyFunction (mathematics)Atmospheric model01 natural sciencessymbols.namesakeKernel (statistics)Lookup tableRadiative transfersymbolsGaussian process emulatorGaussian processAlgorithm021101 geological & geomatics engineering0105 earth and related environmental sciencesInterpolation2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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Multioutput Automatic Emulator for Radiative Transfer Models

2018

This paper introduces a methodology to construct emulators of costly radiative transfer models (RTMs). The proposed methodology is sequential and adaptive, and it is based on the notion of acquisition functions in Bayesian optimization. Here, instead of optimizing the unknown underlying RTM function, one aims to achieve accurate approximations. The Automatic Multi-Output Gaussian Process Emulator (AMO-GAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the promising capabilities of the method for the const…

010504 meteorology & atmospheric sciencesComputer scienceFlatness (systems theory)Bayesian optimizationSampling (statistics)02 engineering and technologyFunction (mathematics)Atmospheric model01 natural sciencessymbols.namesakeSampling (signal processing)0202 electrical engineering electronic engineering information engineeringsymbolsRadiative transfer020201 artificial intelligence & image processingGaussian process emulatorGaussian processAlgorithm0105 earth and related environmental sciencesInterpolationIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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Emulation of 2D Hydrodynamic Flood Simulations at Catchment Scale Using ANN and SVR

2021

Two-dimensional (2D) hydrodynamic models are one of the most widely used tools for flood modeling practices and risk estimation. The 2D models provide accurate results

Computer scienceProcess (engineering)Geography Planning and DevelopmentAquatic ScienceMachine learningcomputer.software_genreBiochemistrysupport vector regressionTD201-500Uncertainty analysisWater Science and TechnologyEmulationArtificial neural networkFlood mythWater supply for domestic and industrial purposesbusiness.industryDimensionality reductionHydraulic engineeringSupport vector machineemulatorsVDP::Teknologi: 500Sample size determinationerror structureArtificial intelligencetraining set sizebusinessTC1-978computerartificial neural networkWater
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FPGA implementation of a fuel cell emulator

2010

Fuel cell based systems are usually tested with the aid of high-cost and complex auxiliary devices. A fuel cell emulator is an attractive solution for preliminary downward system test. The emulator replaces the effective power source saving cost, volume and hydrogen reserve still ensuring high-accuracy of test results. The use of a highperformance fuel cell model is essential for a successful conclusion of the overall design process. Although the proposed emulator is suitable for each fuel cell type and power level, a 10W Proton Exchange Membrane Fuel Cell emulator is designed and tested. An FPGA based controller models the fuel cell steady-state and dynamic behaviour, including temperature…

Engineeringbusiness.industryInterface (computing)fuel cell emulator FPGASystem testingProton exchange membrane fuel cellProcess designSettore ING-INF/01 - ElettronicaModeling and simulationControl theorybusinessField-programmable gate arrayMATLABcomputerSimulationcomputer.programming_language
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Simulation model of a molten carbonate fuel cellemicroturbine hybrid system

2011

A Hybrid System based on High Temperature Fuel Cells coupled to a Microturbine allows a high efficiency, low environmental pollution and it may be exploited as a CHP System producing heat and electricity both Grid Connected and Stand Alone; the overall electrical efficiency could reach a very high value (up to 60%) and total efficiency could be over 70% including the contribution due to heat recovery. In the context of wide research activities of ENEA on High Temperature Fuel Cells and Hybrid Systems e that involve materials, system BoP and fuels e a very great effort has been devoted to design and build, in the ENEA Research Centre of “Casaccia”, an experimental Test-Rig based on a Molten …

Engineeringbusiness.industryNuclear engineeringEnergy Engineering and Power TechnologyEnvironmental pollutionContext (language use)MCFCMicroturbineIndustrial and Manufacturing EngineeringEmulatorlaw.inventionHybrid systemlawHybrid systemElectrical networkHeat recovery ventilationMolten carbonate fuel cellSettore ING-IND/10 - Fisica Tecnica IndustrialeElectric powerbusinessElectrical efficiencySimulationSimulation
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Active emulation of computer codes with Gaussian processes – Application to remote sensing

2020

Many fields of science and engineering rely on running simulations with complex and computationally expensive models to understand the involved processes in the system of interest. Nevertheless, the high cost involved hamper reliable and exhaustive simulations. Very often such codes incorporate heuristics that ironically make them less tractable and transparent. This paper introduces an active learning methodology for adaptively constructing surrogate models, i.e. emulators, of such costly computer codes in a multi-output setting. The proposed technique is sequential and adaptive, and is based on the optimization of a suitable acquisition function. It aims to achieve accurate approximations…

FOS: Computer and information sciencesComputer Science - Machine LearningActive learningActive learning (machine learning)Computer sciencemedia_common.quotation_subjectMachine Learning (stat.ML)Radiative transfer model02 engineering and technology01 natural sciencesMachine Learning (cs.LG)symbols.namesakeArtificial IntelligenceStatistics - Machine Learning0103 physical sciences0202 electrical engineering electronic engineering information engineeringCode (cryptography)Emulation010306 general physicsFunction (engineering)Gaussian processGaussian process emulatorGaussian processRemote sensingmedia_commonEmulationbusiness.industrySampling (statistics)Remote sensingSignal ProcessingGlobal Positioning Systemsymbols020201 artificial intelligence & image processingComputer codeComputer Vision and Pattern RecognitionbusinessHeuristicsSoftwareDesign of experimentsPattern Recognition
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Improving MLC flash performance and endurance with extended P/E cycles

2015

The traditional usage pattern for NAND flash memory is the program/erase (P/E) cycle: the flash pages that make a flash block are all programmed in order and then the whole flash block needs to be erased before the pages can be programmed again. The erase operations are slow, wear out the medium, and require costly garbage collection procedures. Reducing their number is therefore beneficial both in terms of performance and endurance. The physical structure of flash cells limits the number of opportunities to overcome the 1 to 1 ratio between programming and erasing pages: a bit storing a logical 0 cannot be reprogrammed to a logical 1 before the end of the P/E cycle. This paper presents a t…

Hardware_MEMORYSTRUCTURESFlash memory emulatorMulti-level cellComputer scienceNand flash memorybusiness.industryLogic gateNAND gateLatency (engineering)businessComputer hardwareFlash file systemGarbage collection2015 31st Symposium on Mass Storage Systems and Technologies (MSST)
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AI for Resource Allocation and Resource Allocation for AI: a two-fold paradigm at the network edge

2022

5G-and-beyond and Internet of Things (IoT) technologies are pushing a shift from the classic cloud-centric view of the network to a new edge-centric vision. In such a perspective, the computation, communication and storage resources are moved closer to the user, to the benefit of network responsiveness/latency, and of an improved context-awareness, that is, the ability to tailor the network services to the live user's experience. However, these improvements do not come for free: edge networks are highly constrained, and do not match the resource abundance of their cloud counterparts. In such a perspective, the proper management of the few available resources is of crucial importance to impr…

Internet Of ThingMINLPIoTEdge NetworkPerformance EvaluationLow Power Wide Area NetworkSystem ModelingSettore ING-INF/03 - TelecomunicazioniUAVSoftware Defined RadioReal TestbedVehicular NetworkMLLoRaReinforcement LearningResource AllocationMachine LearningGame TheoryArtificial IntelligenceAILPWANColosseum Channel EmulatorChannel EmulationEmulationSDR
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Demo - A Cell-level Traffic Generator for LoRa Networks

2017

In this demo we present and validate a LoRa cell traffic generator, able to emulate the behavior of thousands of low-rate sensor nodes deployed in the same cell, by using a single Software Defined Radio (SDR) platform. Differently from traditional generators, whose goal is creating packet flows which emulate specific applications and protocols, our focus is generating a combined radio signal, as seen by a gateway, given by the super-position of the signals transmitted by multiple sensors simultaneously active on the same channel. We argue that such a generator can be of interest for testing different network planning solutions for LoRa networks.

IoTGenerator (computer programming)cell emulatorSettore ING-INF/03 - TelecomunicazioniComputer sciencebusiness.industryNetwork packet05 social sciences020206 networking & telecommunications02 engineering and technologySoftware-defined radioLoRaLoRaWANNetwork planning and designDefault gateway0502 economics and business0202 electrical engineering electronic engineering information engineeringWirelessSDRbusinessTraffic generation model050203 business & managementComputer networkCommunication channelProceedings of the 23rd Annual International Conference on Mobile Computing and Networking - MobiCom 17
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Physics-Aware Gaussian Processes for Earth Observation

2017

Earth observation from satellite sensory data pose challenging problems, where machine learning is currently a key player. In recent years, Gaussian Process (GP) regression and other kernel methods have excelled in biophysical parameter estimation tasks from space. GP regression is based on solid Bayesian statistics, and generally yield efficient and accurate parameter estimates. However, GPs are typically used for inverse modeling based on concurrent observations and in situ measurements only. Very often a forward model encoding the well-understood physical relations is available though. In this work, we review three GP models that respect and learn the physics of the underlying processes …

MatemáticasEstimation theory0211 other engineering and technologiesContext (language use)02 engineering and technologyMissing dataBayesian statisticssymbols.namesakeKernel method0202 electrical engineering electronic engineering information engineeringsymbolsGeología020201 artificial intelligence & image processingGaussian process emulatorGaussian processAlgorithm021101 geological & geomatics engineeringInterpolation
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