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Trauth, Martin H.: Python-Rezepte für die Geowissenschaften / von Martin H. Trauth. - 1st ed. 2023.. - Berlin, Heidelberg: Springer Berlin Heidelberg, 2023.. - 1 Online-Ressource(XIV, 480 S. 199 Abb., 112 Abb. in Farbe.), ISBN 978-3-662-68118-3 DOI: 10.1007/978-3-662-68118-3
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Geostatistics Toronto 2021 : Quantitative Geology and Geostatistics / edited by Sebastian Alejandro Avalos Sotomayor, Julian M. Ortiz, R. Mohan Srivastava. - 1st ed. 2023.. - Cham: Springer International Publishing, 2023.. - 1 Online-Ressource(XVII, 281 p. 146 illus., 129 illus. in color.), ISBN 978-3-031-19845-8 (Springer Proceedings in Earth and Environmental Sciences) DOI: 10.1007/978-3-031-19845-8
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Benndorf, Jörg: Angewandte Geodatenanalyse und -Modellierung : Eine Einführung in die Geostatistik für Geowissenschaftler und Geoingenieure / von Jörg Benndorf. - 1st ed. 2023.. - Wiesbaden: Springer Fachmedien Wiesbaden, 2023.. - 1 Online-Ressource(XII, 357 S. 171 Abb., 149 Abb. in Farbe.), ISBN 978-3-658-39981-8 (erfolgreich studieren) DOI: 10.1007/978-3-658-39981-8
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Wollschläger, Daniel: R kompakt : der schnelle Einstieg in die Datenanalyse / Daniel Wollschläger. - 3. Auflage. - Berlin ; [Heidelberg]: Springer Spektrum, [2021]. - 1 Online-Ressource (XV, 250 Seiten) : Illustrationen, ISBN 978-3-662-63075-4 (Springer eBook Collection) DOI: 10.1007/978-3-662-63075-4
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Trauth, Martin H.: MATLAB®-Rezepte für die Geowissenschaften / Martin H. Trauth. - Berlin ; [Heidelberg]: Springer Spektrum, [2022]. - 1 Online-Ressource (XII, 544 Seiten), ISBN 978-3-662-64357-0 (Springer eBook Collection) DOI: 10.1007/978-3-662-64357-0
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Freeden, Willi: Exploratory Potential Methods in Geothermal Power Generation : A Survey on Innovative Gravimetry and Magnetometry / by Willi Freeden, Helga Nutz. - 1st ed. 2024.. - Cham: Springer Nature Switzerland, 2024.. - 1 Online-Ressource(XXVI, 207 p. 1 illus.), ISBN 978-3-031-54412-5 (Lecture Notes in Geosystems Mathematics and Computing) DOI: 10.1007/978-3-031-54412-5
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Artificial Intelligent Approaches in Petroleum Geosciences / edited by Constantin Cranganu. - 2nd ed. 2024.. - Cham: Springer International Publishing, 2024.. - 1 Online-Ressource(XVIII, 277 p. 176 illus., 166 illus. in color.), ISBN 978-3-031-52715-9 DOI: 10.1007/978-3-031-52715-9
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Wu, Jiaping: Quantitative analysis and modeling of earth and environmental data : space-time and spacetime data considerations / Jiaping Wu, Junyu He, George Christakos. - Amsterdam ; Kidlington, Oxford ; Cambridge, MA: Elsevier, [2022]. - 1 Online-Ressource (x, 492 Seiten) : Illustrationen, ISBN 978-0-12-816342-9 DOI: 10.1016/C2018-0-00055-9
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Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV) / edited by Seon Ki Park, Liang Xu. - 1st ed. 2022.. - Cham: Springer International Publishing, 2022.. - 1 Online-Ressource(XXI, 705 p. 239 illus., 224 illus. in color.), ISBN 978-3-030-77722-7 (Springer eBook Collection) DOI: 10.1007/978-3-030-77722-7
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Encyclopedia of Mathematical Geosciences / edited by B. S. Daya Sagar, Qiuming Cheng, Jennifer McKinley, Frits Agterberg. - 1st ed. 2023.. - Cham: Springer International Publishing, 2023.. - 1 Online-Ressource(555 illus., 344 illus. in color. eReference.), ISBN 978-3-030-85040-1 (Encyclopedia of Earth Sciences Series) DOI: 10.1007/978-3-030-85040-1
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Aggarwal, Charu C.: Neural Networks and Deep Learning : A Textbook / by Charu C. Aggarwal. - 2nd ed. 2023.. - Cham: Springer International Publishing, 2023.. - 1 Online-Ressource(XXIV, 529 p. 150 illus., 22 illus. in color.), ISBN 978-3-031-29642-0 DOI: 10.1007/978-3-031-29642-0
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Reddy, T. Agami: Applied Data Analysis and Modeling for Energy Engineers and Scientists / by T. Agami Reddy, Gregor P. Henze. - 2nd ed. 2023.. - Cham: Springer International Publishing, 2023.. - 1 Online-Ressource(XXI, 609 p. 400 illus., 194 illus. in color.), ISBN 978-3-031-34869-3 DOI: 10.1007/978-3-031-34869-3
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Zhdanov, Michael S.: Advanced Methods of Joint Inversion and Fusion of Multiphysics Data / by Michael S. Zhdanov. - 1st ed. 2023.. - Singapore: Springer Nature Singapore, 2023.. - 1 Online-Ressource(XVI, 369 p. 52 illus., 37 illus. in color.), ISBN 978-981-9967-22-3 (Advances in Geological Science) DOI: 10.1007/978-981-99-6722-3
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Petrelli, Maurizio: Machine Learning for Earth Sciences : Using Python to Solve Geological Problems / by Maurizio Petrelli. - 1st ed. 2023.. - Cham: Springer International Publishing, 2023.. - 1 Online-Ressource(XVI, 209 p. 102 illus., 99 illus. in color.), ISBN 978-3-031-35114-3 (Springer Textbooks in Earth Sciences, Geography and Environment) DOI: 10.1007/978-3-031-35114-3
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Ehteram, Mohammad: Estimating Ore Grade Using Evolutionary Machine Learning Models / by Mohammad Ehteram, Zohreh Sheikh Khozani, Saeed Soltani-Mohammadi, Maliheh Abbaszadeh. - 1st ed. 2023.. - Singapore: Springer Nature Singapore, 2023.. - 1 Online-Ressource(XIII, 101 p. 45 illus., 39 illus. in color.), ISBN 978-981-19-8106-7 DOI: 10.1007/978-981-19-8106-7
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Advanced Remote Sensing for Urban and Landscape Ecology / edited by Sk. Mustak, Dharmaveer Singh, Prashant Kumar Srivastava. - 1st ed. 2023.. - Singapore: Springer Nature Singapore, 2023.. - 1 Online-Ressource(XIII, 317 p. 153 illus., 129 illus. in color.), ISBN 978-981-9930-06-7 (Advances in Geographical and Environmental Sciences) DOI: 10.1007/978-981-99-3006-7
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High performance computing and artificial intelligence for geosciences / editors Yuzhu Wang, Jinrong Jiang, Yangang Wang. - Basel: MDPI - Multidisciplinary Digital Publishing Institute, 2023. - 1 Online-Ressource (vii, 178 Seiten) : Illustrationen, Diagramme, Karten, ISBN 978-3-0365-8181-1
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Ramdani, Fatwa: Exploring the earth with QGIS : a guide to using satellite imagery at its full potential / by Fatwa Ramdani. - Cham: Springer Nature Switzerland, 2023. - 1 Online-Ressource(xix, 232 Seiten) : Illustrationen, ISBN 978-3-031-46042-5 (Springer Remote Sensing/Photogrammetry) DOI: 10.1007/978-3-031-46042-5
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Liemohn, Michael W.: Data analysis for the geosciences : essentials of uncertainty, comparison, and visualization / Michael W. Liemohn (University of Michigan, USA). - Hoboken, NJ: Wiley Blackwell, 2024. - xxiii, 424 Seiten : Illustrationen, Diagramme, ISBN 978-1-119-74787-1 (Advanced textbook ; 5)
Buch/keine Angabe
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Signatur: UBN/TG 1111 L719
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Wang, Lijing: Data science for the geosciences / Lijing Wang (Lawrence Berkeley National Lab, California), Zhen Yin (Stanford University, California)… . - Cambridge ; New York, NY ; Port Melbourne, VIC ; New Delhi ; Singapore: Cambridge University Press, 2024. - xiii, 244 Seiten, 8 ungezählte Seiten Bildtafeln : Illustrationen, Diagramme, ISBN 978-1-009-20141-4
Buch/keine Angabe
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Signatur: UBN/TG 1111 W246
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