@inproceedings{
 title = {A hybrid intelligent system clonart for short and mid-term forecasting for the brazilian energy distribution system},
 type = {inproceedings},
 year = {2008},
 id = {8fd4ac6d-baf3-39ee-97cf-7c914fbbe6d2},
 created = {2019-02-14T18:02:01.111Z},
 file_attached = {false},
 profile_id = {74e7d4ea-3dac-3118-aab9-511a5b337e8f},
 last_modified = {2019-02-14T18:02:01.111Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {The present work describes an application of Clonart (Clonal Adaptive Resonance Theory) for forecasting of amount of precipitation for the Brazilian Energy Distribution System. The effectiveness of the Brazilian electricity system directly depends on the difference between hydroelectric energy production and consumer use. Production depends upon the volume of water stored in the reservoirs. A forecasting system for the amount of rainfall throughout the year contributes significantly to the analysis. The plasticity of the Clonart ensures that a new piece of knowledge does not overshadow previous knowledge. This is especially important for forecast problems because this type of problem needs constants training. © 2008 IEEE.},
 bibtype = {inproceedings},
 author = {Alexandrino, J.L. and Zanchettin, C. and De Barros Carvalho Filho, E.C.},
 doi = {10.1109/IJCNN.2008.4634295},
 booktitle = {Proceedings of the International Joint Conference on Neural Networks}
}

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