Monthly Precipitation Forecasting with a Neuro-Fuzzy Model

Changsam Jeong, Ju-Young Shin, Taesoon Kim and Jun-Haneg Heo ()

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2012, vol. 26, issue 15, 4467-4483

Abstract: Quantitative and qualitative monthly precipitation forecasts are produced with ANFIS. To select the proper input variable set from 30 variables, including climatological and hydrological monthly recording data, the forward selection method, which is a wrapper method for feature selection, is applied. The error analysis of the results from training and checking the data sets suggests that 3 variables can be used as a suitable number of inputs for ANFIS, and the best five 3-input-variable sets were selected. The quantitative monthly precipitation forecasts were computed using each 3-input-variable set, and the ensemble averaging method over the five forecasts was used for calculations to reduce the uncertainties in the forecasts and to remove the negative rainfall forecasts. A qualitative forecast that is computed with the quantitative forecast also produced three types of categories that describe the next month’s precipitation condition and was compared with data from the weather agency of Korea. Copyright Springer Science+Business Media Dordrecht 2012

Keywords: Neuro-fuzzy; Input data selection; ANFIS; Long-term forecast (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11269-012-0157-3 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:26:y:2012:i:15:p:4467-4483

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11269

DOI: 10.1007/s11269-012-0157-3

Access Statistics for this article

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) is currently edited by G. Tsakiris

More articles in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) from Springer, European Water Resources Association (EWRA)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().