Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Omid Orang"'
Publikováno v:
Learning and Nonlinear Models. 19:29-50
Time series forecasting is a powerful tool in planning and decision making, from traditional statistical models to soft computing and artificial intelligence approaches several methods have been developed to generate increasingly accurate forecasts.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b0270aaa47849b4116be84ea33d38280
https://doi.org/10.21528/lnlm-vol19-no2-art3
https://doi.org/10.21528/lnlm-vol19-no2-art3
Autor:
Hugo Vinicius Bitencourt, Omid Orang, Luiz Augusto Facury de Souza, Petrônio C. L. Silva, Frederico Gadelha Guimarães
Publikováno v:
Neural Computing and Applications. 35:9407-9420
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e7c17e43158da403c0f45a975755546
https://doi.org/10.1007/s00521-022-08120-5
https://doi.org/10.1007/s00521-022-08120-5
Publikováno v:
Neurocomputing. 512:153-177
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3409b18f6abaf108a8189ab55845ba0b
https://doi.org/10.1016/j.neucom.2022.09.030
https://doi.org/10.1016/j.neucom.2022.09.030
Among various soft computing approaches for time series forecasting, Fuzzy Cognitive Maps (FCM) have shown remarkable results as a tool to model and analyze the dynamics of complex systems. FCM have similarities to recurrent neural networks and can b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c73d39fca651fcb57c93765c06fb67b7
Publikováno v:
FUZZ-IEEE
Various studies indicate that Fuzzy Time Series (FTS) methods can obtain high accuracy in a variety of forecasting applciations. However, weighted FTS methods tend to show superiority in contrast to weightless ones. This study exploits the use of Fuz
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9284ddf492e1e15b3dcd9c41c7226ee6
https://doi.org/10.1109/fuzz48607.2020.9177767
https://doi.org/10.1109/fuzz48607.2020.9177767
Publikováno v:
Energy. 57:382-401
In this paper, WESN (wavelet echo state network) with a novel ESN-based reconstruction stage is applied to both STLF (short-term load forecasting) and STTF (short-term temperature forecasting). Wavelet transform is used as the front stage for multi-r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4d473b76d0153c76c44bd6c2e698e74e
https://doi.org/10.1016/j.energy.2013.06.007
https://doi.org/10.1016/j.energy.2013.06.007