Soft computing tools in rainfall-runoff modeling
DSpace at IIT Bombay
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Title |
Soft computing tools in rainfall-runoff modeling
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Creator |
Jothiprakash, V
Magar, R |
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Subject |
Rainfall-runoff process
soft computing techniques artificial neural network genetic programming adaptive neuro fuzzy inferene system |
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Description |
The use of rainfall-runoff models in the decision making process of water resources planning and management has become increasingly indispensable. Rainfall-runoff modeling in the broad sense started at the end of 19th century and till today there are various types of models based on their mechanism, input data and other modeling requirements. These type of models range from physical, conceptual, empirical models and more sophisticated models like Artificial Neural Network (ANN), Adaptive Neuro Fuzzy Inference System (ANFIS), Genetic Programming (GP), Model Tree (MT), Support Vector Machine (SVM) and recently Chaos theory. The primary aim of this paper is to review the recent works on Rainfall-Runoff modeling using soft computing techniques.
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Publisher |
Indian Society for Hydraulics
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Date |
2012-09-12T11:01:30Z
2012-09-12T11:01:30Z 2009 |
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Type |
Article
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Identifier |
ISH Journal of Hydraulic Engineering, 15(SP1) 84-96
2164-3040 http://dspace.library.iitb.ac.in/jspui/handle/100/14400 |
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Language |
English
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