@prefix dcat: <http://www.w3.org/ns/dcat#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix vcard: <http://www.w3.org/2006/vcard/ns#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-hal-00698582v1> a dcat:Dataset ;
    dct:description """
              We consider the problem of rapidly identifying, among a large set of candidate parameter fields, a subset of candidates whose responses computed by accurate forward flow and transport simulation match a reference response curve. In order to keep the number of calls to the flow simulator computationally tractable, a recent distance-based approach relying on fast proxy simulations is revisited, and turned into a non-stationary Kriging method. The covariance kernel is obtained by combining a classical kernel with the proxy function, hence generalizing the idea of random field deformation to high-dimensional Computer Experiments. Once the accurate simulator has been run for an initial subset of models and a Kriging metamodel has been inferred, the predictive distributions of misfits for the remaining geological models can be used as a guide to solve the inverse problem in a sequential way. The proposed algorithm, Proxy-based Kriging for Sequential Inversion (PROKSI), relies indeed on a variant of the Expected Improvement, a popular criterion for Kriging-based global optimization. A statistical benchmark of ProKSI's performances finally illustrates the efficiency and the robustness of the approach when using different kinds of proxies.
            """ ;
    dct:identifier "hal-00698582" ;
    dct:issued "2026-05-18T09:47:35.670283"^^xsd:dateTime ;
    dct:language "en" ;
    dct:modified "2026-05-18T09:47:35.670289"^^xsd:dateTime ;
    dct:publisher <https://rec.harvest-normandie.data4citizen.com/organization/cce9db95-46d9-4dc2-84b6-764215d0a002> ;
    dct:title "Distance-based Kriging relying on proxy simulations for inverse conditioning" ;
    dcat:contactPoint [ a vcard:Organization ;
            vcard:fn "CCSD" ] ;
    dcat:distribution <https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-hal-00698582v1/resource/82e2bd09-17f2-4a76-91ca-0d686a3ae396> ;
    dcat:keyword "infoeu-reposemanticspreprint",
        "infoinfo-mocomputer-science-csmodeling-and-simulation",
        "preprints-working-papers-",
        "sdustusciences-of-the-universe-physicsearth-sciences",
        "statapstatistics-statapplications-statap",
        "statmlstatistics-statmachine-learning-statml" ;
    dcat:landingPage <https://hal.science/hal-00698582> .

<https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-hal-00698582v1/resource/82e2bd09-17f2-4a76-91ca-0d686a3ae396> a dcat:Distribution ;
    dct:format "HTML" ;
    dct:issued "2026-05-18T09:47:35.731214"^^xsd:dateTime ;
    dct:modified "2026-05-18T09:47:35.650693"^^xsd:dateTime ;
    dct:title "Distance-based Kriging relying on proxy simulations for inverse conditioning" ;
    dcat:accessURL <https://hal.science/hal-00698582> .

<https://rec.harvest-normandie.data4citizen.com/organization/cce9db95-46d9-4dc2-84b6-764215d0a002> a foaf:Agent ;
    foaf:name "test_moissonnage_selune" .

<https://hal.science/hal-00698582> a foaf:Document .