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1. |
Record Nr. |
UNINA9910348257503321 |
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Autore |
Adam Jean-Michel |
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Titolo |
Récit et connaissance / / François Laplantine, Joseph Lévy, Jean-Baptiste Martin, Alexis Nouss |
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Pubbl/distr/stampa |
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Lyon, : Presses universitaires de Lyon, 2018 |
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ISBN |
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Descrizione fisica |
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1 online resource (328 p.) |
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Altri autori (Persone) |
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AlmeidaMiguel Vale de |
BernardRégis |
CercletDenis |
ChissJean-Louis |
ComellesJosep M |
DumouchelPaul |
FerreiraJerusa Pires |
GelasBruno |
JacquinPhilippe |
LaéJean-François |
LaplantineFrançois |
LemieuxRaymond |
LévyJoseph |
LévyJoseph J |
MartinJean-Baptiste |
MeintelDeirdre |
NoussAlexis |
PandolfiMariella |
PordeusIsmael |
RobinRégine |
SavardRémy |
SilvaJosé Carlos Gomes da |
SimonSherry |
VieiraNelson H |
ZupancicMetka |
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Soggetti |
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Literary Theory & Criticism |
Anthropology |
récit |
mythe |
utopie |
narration |
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littérature |
fiction |
sociologie |
interdiscipline |
connaissance |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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Après un long déclin consécutif aux bouleversements idéologiques des xviie et xviiie siècles, le récit redevient, sous des formes nouvelles, vecteur et facteur de connaissance. Les contributions de vingt-cinq chercheurs américains et européens travaillant dans des disciplines aussi diverses que l'anthropologie, la sociologie, les études littéraires, la linguistique, le journalisme, examinent comment la réémergence du récit est susceptible d'entraîner la redéfinition et la valorisation d'une connaissance qui ne serait plus contrainte par les normes de la rationalité et de l'objectivité qui ont soutenu l'idéologie scientifique. |
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2. |
Record Nr. |
UNINA9910877036303321 |
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Titolo |
Advanced mapping of environmental data : geostatistics, machine learning, and Bayesian maximum entropy / / edited by Mikhail Kanevski |
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Pubbl/distr/stampa |
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London, : ISTE, Ltd. |
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Hoboken, NJ, : J. Wiley, c2008 |
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ISBN |
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9780470611463 (e-book) |
9781848210608 (hbk.) |
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Descrizione fisica |
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1 online resource (xiii, 313 p.) : ill |
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Collana |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Geology - Statistical methods |
Machine learning |
Bayesian statistical decision theory |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Chapter 1. Advanced Mapping of Environmental Data: Introduction -- Chapter 2. Environmental Monitoring Network Characterization and Clustering -- Chapter 3. Geostatistics: Spatial Predictions and Simulations -- Chapter 4. Spatial Data Analysis and Mapping Using Machine Learning Algorithms -- Chapter 5. Advanced Mapping of Environmental Spatial Data: Case Studies -- Chapter 6. Bayesian Maximum Entropy – BME -- Index. |
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Sommario/riassunto |
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This book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more. |
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