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http://dx.doi.org/10.3741/JKWRA.2016.49.10.877

ROC evaluation for MLP ANN drought forecasting model  

Jeong, Min-Su (Disaster Management Research Center)
Kim, Jong-Suk (Dept. of Civil Engineering, University of Seoul)
Jang, Ho-Won (Dept. of Civil Engineering, Joongbu University)
Lee, Joo-Heon (Dept. of Civil Engineering, Joongbu University)
Publication Information
Journal of Korea Water Resources Association / v.49, no.10, 2016 , pp. 877-885 More about this Journal
Abstract
In this study, the Standard Precipitation Index(SPI), meteorological drought index, was used to evaluate the temporal and spatial assessment of drought forecasting results for all cross Korea. For the drought forecasting, the Multi Layer Perceptron-Artificial Neural Network (MLP-ANN) was selected and the drought forecasting was performed according to different forecasting lead time for SPI (3) and SPI (6). The precipitation data observed in 59 gaging stations of Korea Meteorological Adminstration (KMA) from 1976~2015. For the performance evaluation of the drought forecasting, the binary classification confusion matrix, such as evaluating the status of drought occurrence based on threshold, was constituted. Then Receiver Operating Characteristics (ROC) score and F score according to conditional probability are computed. As a result of ROC analysis on forecasting performance, drought forecasting performance, of applying the MLP-ANN model, shows satisfactory forecasting results. Consequently, two-month and five-month leading forecasts were possible for SPI (3) and SPI (6), respectively.
Keywords
Meteorological Drought; Standardized Precipitation Index (SPI); MLP ANN; ROC; F score;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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