Mathematical Geosciences : Hybrid Symbolic-Numeric Methods

Lingua: inglese

Editore: Springer, 2023

3030924947 / 9783030924942

Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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Venditore AbeBooks dal 14 agosto 2006

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Druck auf Anfrage Neuware - Printed after ordering - This second edition of Mathematical Geosciences book adds five new topics: Solution equations with uncertainty, which proposes two novel methods for solving nonlinear geodetic equations as stochastic variables when the parameters of these equations have uncertainty characterized by probability distribution. The first method, an algebraic technique, partly employs symbolic computations and is applicable to polynomial systems having different uncertainty distributions of the parameters. The second method, a numerical technique, uses stochastic differential equation in Ito form; Nature Inspired Global Optimization where Meta-heuristic algorithms are based on natural phenomenon such as Particle Swarm Optimization. This approach simulates, e.g., schools of fish or flocks of birds, and is extended through discussion of geodetic applications. Black Hole Algorithm, which is based on the black hole phenomena is added and a new variant of the algorithm code is introduced and illustrated based on examples; The application of the Gröbner Basis to integer programming based on numeric symbolic computation is introduced and illustrated by solving some standard problems; An extension of the applications of integer programming solving phase ambiguity in Global Navigation Satellite Systems (GNSSs) is considered as a global quadratic mixed integer programming task, which can be transformed into a pure integer problem with a given digit of accuracy. Three alternative algorithms are suggested, two of which are based on local and global linearization via McCormic Envelopes; and Machine learning techniques (MLT) that offer effective tools for stochastic process modelling. The Stochastic Modelling section is extended by the stochastic modelling via MLT and their effectiveness is compared with that of the modelling via stochastic differential equations (SDE). Mixing MLT with SDE also known as frequently Neural Differential Equations is also introduced and illustratedby an image classification via a regression problem.

Codice articolo 9783030924942

Titolo
Mathematical Geosciences : Hybrid Symbolic-Numeric Methods
Autore
Robert H. Lewis
Editore
Springer
Anno di pubblicazione
2023
Condizione
Neu
Rilegatura
Buch
Lingua
inglese
ISBN 10
3030924947
ISBN 13
9783030924942
Edizione
seconda edizione
Peso dell'articolo
1409 grammi
Dimensioni
241x160x43 mm

AHA-BUCH GmbH

Einbeck, Germania

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

Tariffe di spedizione da Germania a U.S.A.

ArticoloDa 7 a 10 giorni lavorativiDa 5 a 7 giorni lavorativi
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