Data-Driven Modelling

Data-Driven Modelling

Sohail Ahmed Tufail

Autore: Sohail Ahmed Tufail
Formato: Copertina flessibile
Pagine: 68
Data Pubblicazione: 2017-08-10
Edizione: 1
Lingua: English

Descrizione:
The advantage of statistical models of inputoutput type is that they can be relatively easily constructed and applied, but on the other hand the disadvantage of such models is that that they dont reveal the inner nature of observed phenomenon. Conceptual models, which have advantage of transparent functioning, but are sometimes hard to be proven correct. Artificial intelligence offers methods of machine learning from examples, which eliminate the disadvantages of statistical as well as conceptual approaches and integrate the advantages. A comprehensive data driven modelling experiment based on regression trees is presented in this book. Regression trees have been employed on practical problem of constructing a data driven model for runoff prediction from known present and past runoff at waterlevelgauges and rainfall at rain gauges within the catchment. Results based on approximation and prediction accuracy obtained from regression trees are then compared with other DDM techniques namely, artificial neural networks, Gaussian process, support vector regressions and multiple linear regressions. Book is a must read for the researchers working in the field of datadriven modelling.