Bookcover of Hydrological Predictions
Booktitle:

Hydrological Predictions

Using Data-Driven Models Coupled with Data Preprocessing Techniques

LAP LAMBERT Academic Publishing (2011-05-31 )

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ISBN-13:

978-3-8433-6446-1

ISBN-10:
384336446X
EAN:
9783843364461
Book language:
English
Blurb/Shorttext:
This book makes an endeavor to improve the accuracy of hydrological forecasting in three aspects, model inputs, selection of models, and data-preprocessing techniques. Seven input techniques, namely, linear correlation analysis (LCA), false nearest neighbors, correlation integral, stepwise linear regression, average mutual information, partial mutual information, artificial neural network (ANN) based on multi-objective genetic algorithm, are first examined to select optimal model inputs in each prediction scenario. Representative models, such as K-nearest-neighbors (K-NN) model, dynamic system based model (DSBM), ANN, modular ANN (MANN), and hybrid artificial neural network-support vector regression (ANN-SVR), are then proposed to conduct rainfall and streamflow forecasts. Four data-preprocessing methods including moving average (MA), principal component analysis (PCA), singular spectrum analysis (SSA), and wavelet analysis (WA), are further investigated by integration with the abovementioned forecasting models.
Publishing house:
LAP LAMBERT Academic Publishing
Website:
https://www.lap-publishing.com/
By (author) :
Kwok-wing Chau, Cong-lin Wu
Number of pages:
248
Published on:
2011-05-31
Stock:
Available
Category:
Building and environmental technology
Price:
79.00 €
Keywords:
Hydrological Predictions, data-driven models, Data Preprocessing Techniques, Artificial Intelligence Techniques, Soft Computing, rainfall, Streamflow, Rainfall-Runoff, Hydrological Model, Hydrological Forecasting

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