| dc.creator |
Kucukyaman, Derya |
|
| dc.creator |
Terzi, Oezlem |
|
| dc.creator |
KESKİN, Mustafa Erol |
|
| dc.creator |
TAYLAN, Emine Dilek |
|
| dc.date |
2008-12-31T22:00:00Z |
|
| dc.date.accessioned |
2020-10-06T11:26:25Z |
|
| dc.date.available |
2020-10-06T11:26:25Z |
|
| dc.identifier |
e03bfe2b-b5a5-4deb-befc-6c17778aa1ab |
|
| dc.identifier |
10.1623/hysj.54.6.1114 |
|
| dc.identifier |
https://avesis.sdu.edu.tr/publication/details/e03bfe2b-b5a5-4deb-befc-6c17778aa1ab/oai |
|
| dc.identifier.uri |
http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/74181 |
|
| dc.description |
Droughts may be classified as meteorological, hydrological or agricultural. When meteorological drought appears in a region, agricultural and hydrological droughts follow. In this study, the standardized precipitation index (SPI) was applied for meteorological drought analysis at nine stations located around the Lakes District, Turkey. Analyses were performed on 3-, 6-, 9- and 12-month-long data sets. The SPI drought classifications were modelled by Adaptive Neural-Based Fuzzy Inference System (ANFIS) and Fuzzy Logic, which has the advantage that, in contrast to most of the time series modelling techniques, it does not require the model structure to be known a priori. Comparison of the observed values and the modelling results shows a better agreement with SPI-12 and ANFIS models than with fuzzy logic models. |
|
| dc.language |
eng |
|
| dc.rights |
info:eu-repo/semantics/closedAccess |
|
| dc.title |
Meteorological drought analysis using data-driven models for the Lakes District, Turkey |
|
| dc.type |
info:eu-repo/semantics/article |
|