Bonakdari, Hossein <br/><br/>
Machine learning in earth, environmental and planetary sciences: theoretical and practical applications 

 - Cambridge  Elsevier  2023 
 - xvii, 370 p.  ilus. 
<br/><br/>Incluye referencias bibliográficas e índice<br/><br/> 
<br/><br/>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 
<br/><br/><label>ISBN: </label>978-0-443-15284-9 
<br/><br/><label>Subjects--Topical Terms: </label><br/>CIENCIAS DE LA TIERRA<br/>CIENCIAS AMBIENTALES<br/>APRENDIZAJE AUTOMATICO<br/>ANALISIS DE DATOS