Procjena točnosti ANFIS-a u prognoziranju lebdećeg nanosa

Autor:	Hamed Rouhani, Seyed Morteza Seyedian
Rok vydání:	2015
Předmět:	Adaptive neuro fuzzy inference system Nonlinear system Identification (information) Mean squared error Computer science Inference system Complex system Geotechnical engineering Data mining computer.software_genre Sediment concentration computer Civil and Structural Engineering
Zdroj:	Journal of the Croatian Association of Civil Engineers. 67:1165-1176
ISSN:	1333-9095 0350-2465
Popis:	Capabilities offered by an adaptive neuro-fuzzy inference system (ANFIS) in the estimation of daily sediment loads at four stations in the USA, are explored in the paper. For this purpose, models with various input combinations of data sets were constructed to enable identification of the best possible structure. The results show that the best ANFIS model exhibits better performance compared to the SRC model, in terms of the RMSE, MBE and R2 values. The results also indicate that the ANFIS model can be applied to facilitate modelling of nonlinear dynamics of complex systems.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7de1a7ad6686a740d72ff80bdb4ba625 https://doi.org/10.14256/jce.1210.2015 Zobrazit plný text záznamu