Machine learning in earth, environmental and planetary sciences: theoretical and practical applications
Por: Bonakdari, Hossein.
Otros Autores: Ebtehaj, Isa | Ladouceur, Joseph D.
Tipo de material: Libro Editor: Cambridge: Elsevier, 2023Descripción: xvii, 370 p. ilus.ISBN: 978-0-443-15284-9.Tema(s): CIENCIAS DE LA TIERRA | CIENCIAS AMBIENTALES | APRENDIZAJE AUTOMATICO | ANALISIS DE DATOSRecurso en línea: Tabla de contenido | Texto Completo
Incluye referencias bibliográficas e índice
Chapter 1: Dataset preparation -- Chapter 2: Preprocessing approaches -- Chapter 3:- Postprocessing approaches -- Chapter 4: Non-tuned single-layer feed-forward neural network learning machine—concept -- Chapter 5: Non-tuned single-layer feed-forward neural network learning machine—coding and implementation -- Chapter 6: Outlier-based models of the non-tuned neural network—concept -- Chapter 7: Outlier-based models of the non-tuned neural network—coding and implementation -- Chapter 8: Online sequential non-tuned neural network—concept -- Chapter 9: Online sequential nontuned neural network—coding and implementation -- Chapter 10: Self-adaptive evolutionary of non-tuned neural network—concept -- Chapter 11: Self-adaptive evolutionary of non-tuned neural network—coding and implementation
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