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In den WarenkorbZustand: New. Über den AutorIoannis Stefanou is Associate Professor and Researcher at Laboratoire Navier, Ecole des Ponts Paris Tech, France. Jean Sulem is Full Professor and Senior Researcher at Laboratoire Navier, Ecole des .
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Buch. Zustand: Neu. Machine Learning in Geomechanics 1 | Overview of Machine Learning, Unervised Learning, Regression, Classification and Artificial Neural Networks | Ioannis Stefanou (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2025 | Wiley | EAN 9781789451924 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Buch. Zustand: Neu. Neuware - Machine learning has led to incredible achievements in many different fields of science and technology. These varied methods of machine learning all offer powerful new tools to scientists and engineers and open new paths in geomechanics. The two volumes of Machine Learning in Geomechanics aim to demystify machine learning. They present the main methods and provide examples of its applications in mechanics and geomechanics. Most of the chapters provide a pedagogical introduction to the most important methods of machine learning and uncover the fundamental notions underlying them. Building from the simplest to the most sophisticated methods of machine learning, the books give several hands-on examples of coding to assist readers in understanding both the methods and their potential and identifying possible pitfalls.
Buch. Zustand: Neu. Neuware - Machine learning has led to incredible achievements in many different fields of science and technology. These varied methods of machine learning all offer powerful new tools to scientists and engineers and open new paths in geomechanics.
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In den WarenkorbZustand: New. 2021. 1st Edition. Hardback. . . . . . Books ship from the US and Ireland.
Buch. Zustand: Neu. Neuware - Instabilities Modeling in Geomechanics describes complex mechanisms which are frequently met in earthquake nucleation, geothermal energy production, nuclear waste disposal and CO2 sequestration. These mechanisms involve systems of non-linear differential equations that express the evolution of the geosystem (e.g. strain localization, temperature runaway, pore pressure build-up, etc.) at different length and time scales.
Buch. Zustand: Neu. Neuware -Machine learning has led to incredible achievements in many different fields of science and technology. These varied methods of machine learning all offer powerful new tools to scientists and engineers and open new paths in geomechanics. The two volumes of Machine Learning in Geomechanics aim to demystify machine learning. They present the main methods and provide examples of its applications in mechanics and geomechanics. Most of the chapters provide a pedagogical introduction to the most important methods of machine learning and uncover the fundamental notions underlying them. Building from the simplest to the most sophisticated methods of machine learning, the books give several hands-on examples of coding to assist readers in understanding both the methods and their potential and identifying possible pitfalls. 272 pp. Englisch.