globalchange  > 气候减缓与适应
DOI: 10.1007/s10584-017-1907-2
Scopus记录号: 2-s2.0-85011586141
论文题名:
Precipitation concentration index management by adaptive neuro-fuzzy methodology
作者: Petković D.; Gocic M.; Trajkovic S.; Milovančević M.; Šević D.
刊名: Climatic Change
ISSN: 0165-0009
EISSN: 1573-1480
出版年: 2017
卷: 141, 期:4
起始页码: 655
结束页码: 669
语种: 英语
Scopus关键词: Forecasting ; Fuzzy neural networks ; Fuzzy systems ; Model predictive control ; Adaptive neuro-fuzzy ; Adaptive neuro-fuzzy inference system ; Concentration indices ; Estimation and predictions ; Precipitation measurement ; Spring precipitation ; Summer precipitation ; Winter precipitation ; Fuzzy inference ; artificial neural network ; fuzzy mathematics ; hydrological modeling ; index method ; methodology ; precipitation (climatology) ; precipitation assessment ; prediction ; regression analysis ; Serbia
英文摘要: This paper reconsiders the precipitation concentration index (PCI) in Serbia using precipitation measurements such as the mean winter precipitation amount, annual total precipitation, mean summer precipitation amount, mean spring precipitation amount, mean autumn precipitation amount and the mean of precipitation for the vegetation period (April–September). Potentials for further improvement of PCI prediction lie in the improvement of current prediction strategies. One of the options is the introduction of model predictive control. To manage the PCI, it is good to select factors or parameters that are the most important for PCI estimation and prediction, i.e. to conduct variable selection procedure. In the present study, a regression based on the adaptive neuro-fuzzy inference system (ANFIS) is applied for selection of the most influential PCI inputs based on the precipitation measurements. The effectiveness of the proposed strategy is verified according to the simulation results. The results show that the mean autumn precipitation amount is the most influential for PCI prediction and estimation and could be used for the simplification of predictive methods to avoid multiple input variables. © 2017, Springer Science+Business Media Dordrecht.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/84057
Appears in Collections:气候减缓与适应
气候变化事实与影响

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作者单位: Pedagogical Faculty in Vranje, University of Niš, Partizanska 14, Vranje, Serbia; Faculty of Civil Engineering and Architecture, University of Nis, Aleksandra Medvedeva 14, Nis, Serbia; Faculty of Mechanical Engineering, University of Nis, Aleksandra Medvedeva 14, Nis, Serbia; Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia

Recommended Citation:
Petković D.,Gocic M.,Trajkovic S.,et al. Precipitation concentration index management by adaptive neuro-fuzzy methodology[J]. Climatic Change,2017-01-01,141(4)
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