Downscaling global weather forecast outputs using ANN for flood prediction.
Do Hoai, Nam, Udo, Keiko, Mano, Akira (2011)
Journal of Applied Mathematics
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Do Hoai, Nam, Udo, Keiko, Mano, Akira (2011)
Journal of Applied Mathematics
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Zhaowei, Shang, Lingfeng, Zhang, Shangjun, Ma, Bin, Fang, Taiping, Zhang (2010)
Mathematical Problems in Engineering
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Richard D. De Veaux (2001)
Journal de la société française de statistique
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Gocheva-Ilieva, S.G., Iliev, I.P. (2010)
Mathematical Problems in Engineering
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Jiří Vomlel (2015)
Kybernetika
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In this paper, we generalize the noisy-or model. The generalizations are three-fold. First, we allow parents to be multivalued ordinal variables. Second, parents can have both positive and negative influences on their common child. Third, we describe how the suggested generalization can be extended to multivalued child variables. The major advantage of our generalizations is that they require only one parameter per parent. We suggest a model learning method and report results of experiments...
Geert Molenberghs, Herbert Thijs, Bart Michiels, Geert Verbeke, Michael G. Kenward (2004)
Journal de la société française de statistique
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Terje Loken, Jan Komorowski (2001)
International Journal of Applied Mathematics and Computer Science
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Traditional data mining methods based on rough set theory focus on extracting models which are good at classifying unseen obj-ects. If one wants to uncover new knowledge from the data, the model must have a high descriptive quality-it must describe the data set in a clear and concise manner, without sacrificing classification performance. Rough modeling, introduced by Kowalczyk (1998), is an approach which aims at providing models with good predictive emphand descriptive qualities, in...
Ham, Frederic M., Kostanic, Ivica (1996)
Mathematical Problems in Engineering
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Sanja Petrović, Ivan Obradović, Radovan Krtolica (1991)
The Yugoslav Journal of Operations Research
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