![](/images/graphics-bg.png)
Review-artificial intelligence based modelling of hydrological processes
Joint Authors
al-Agha, Jawad S.
Said, Muhammad Azlin Muhammad
Mughir, Yunus
Source
Publisher
Islamic University of Gaza Faculty of Engineering
Publication Date
2012-10-31
Country of Publication
Palestine (Gaza Strip)
No. of Pages
13
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
English Abstract
Hydrological processes such as runoff and contaminant transport are usually affected by various complex interrelated variables.
Moreover, uncertainties in variables estimate are the common stamp of these processes.
Due to this complex nature, Physical modeling of any hydrological system requires availability of large, accurate and detailed data related to all influencing variables, which are not always available due to financial and technical constraints.
This may lead to deficiencies in model’s performance which in turn, negatively affect hydrological planning and policy drawing.
To address these shortcomings, artificial intelligence (AI) based techniques have been recently used as alternative tools to traditional physical hydrological models.
These techniques have been proved to be successful and effective in tackling wide spectrum of challenging hydrological processes.
This article is intended to serve as an introductory review of application of two AI techniques namely, artificial neural networks (ANNs) and support vector machine (SVM) in various hydrological applications.
In this article, ANNs and SVM theoretical background coupled with their strength points that make them suitable for hydrological modeling were briefly described.
Moreover, various examples of successful applications of ANNs and SVM for modeling different hydrological processes were also provided.
Data Type
Conference Papers
Record ID
BIM-777337
American Psychological Association (APA)
al-Agha, Jawad S.& Said, Muhammad Azlin Muhammad& Mughir, Yunus. 2012-10-31. Review-artificial intelligence based modelling of hydrological processes. . , pp.1-13.Gaza Palestine : Islamic University of Gaza Faculty of Engineering.
https://search.emarefa.net/detail/BIM-777337
Modern Language Association (MLA)
Mughir, Yunus…[et al.]. Review-artificial intelligence based modelling of hydrological processes. . Gaza Palestine : Islamic University of Gaza Faculty of Engineering. 2012-10-31.
https://search.emarefa.net/detail/BIM-777337
American Medical Association (AMA)
al-Agha, Jawad S.& Said, Muhammad Azlin Muhammad& Mughir, Yunus. Review-artificial intelligence based modelling of hydrological processes. .
https://search.emarefa.net/detail/BIM-777337