Name: The Probabilistic Vision of the Physical World: A Point of View of Earth Sciences (Lecture Notes in Geosystems Mathematics and Computing) (en Inglés)
SKU: 63829473
Price: 2615.55 MXN
Availability: InStock
Author: Fernando Sansò; Alberta Albertella
ISBN: 9783031882678

portada The Probabilistic Vision of the Physical World: A Point of View of Earth Sciences (Lecture Notes in Geosystems Mathematics and Computing) (en Inglés)

The Probabilistic Vision of the Physical World: A Point of View of Earth Sciences (Lecture Notes in Geosystems Mathematics and Computing) (en Inglés)

Formato

Libro Físico

Editorial

Birkhäuser

Autor

Fernando Sansò; Alberta Albertella

Idioma

Inglés

N° páginas

140

Encuadernación

Tapa Blanda

ISBN13

9783031882678

The Probabilistic Vision of the Physical World: A Point of View of Earth Sciences (Lecture Notes in Geosystems Mathematics and Computing) (en Inglés)

Fernando Sansò; Alberta Albertella (Autor) · Birkhäuser · Tapa Blanda

Libro Nuevo Importado

Envío: 13 a 18 días háb.

$ 4,755.55$ 2,615.55

-45%

Costos de importación incluídos en el precio ✅

Libro Nuevo

Quedan más de 100 unidades

$ 2,615.55

¡Envío Gratis! Llega entre el 25 Sep y el 05 Oct a CUAUHTÉMOC, Ciudad de México. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "The Probabilistic Vision of the Physical World: A Point of View of Earth Sciences (Lecture Notes in Geosystems Mathematics and Computing) (en Inglés)"

This book investigates the relationship between empirical reality and theoretical modelling in Earth sciences, focusing on how empirical experiments and theoretical models interact. It explores the connection between statistics and probability theory, emphasizing the importance of these tools in understanding the physical world. The first chapter addresses the frequency-probability antinomy, while the second chapter discusses the sources of randomness in modelling. Chapters 3 and 4 delve into statistical inference, covering estimation theory and testing theory. Chapter 5 examines the relationship between discrete-finite models and continuous-infinite dimensional models, particularly random fields, making the concepts accessible to geodesists and geophysicists. Chapter 6 explores modern machine learning and deep learning, highlighting their roots in traditional statistical methods and neural networks. The book concludes with a caution against relying solely on empirical evidence and "black box" algorithms, advocating for the integration of physical laws with empirical models to advance understanding of the physical world. The book is primarily intended for graduate students and researchers in the field of earth sciences with a basic background in probability theory and statistics.