학술논문
Comparison between inverse modelling and data assimilation to estimate rainfall from runoff using the multilayer perceptron
Document Type
Conference
Author
Source
2015 International Joint Conference on Neural Networks (IJCNN) Neural Networks (IJCNN), 2015 International Joint Conference on. :1-8 Jul, 2015
Subject
Language
ISSN
2161-4393
2161-4407
2161-4407
Abstract
The ability of the multilayer perceptron to model the inverse relation of a fictitious watershed is investigated. Comparison is done between a new formulation of data assimilation and the standard multilayer perceptron applied to three kinds of models: static, feedforward and recurrent. It appears that both techniques are equivalent and allow a very good estimation of the inverse relation. This study aims at proposing methods to supplement or adapt historical databases to modern instrumentation. Datasets will thus be used over a longer time-series to better apprehend the consequences of global warming.