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http://dx.doi.org/10.15683/kosdi.2021.6.30.329

Analysis of Drought Vulnerable Areas using Neural-Network Algorithm  

Shin, Jeong Hoon (Safety Inspection for Infrastructure Laboratory, Advanced Institute of Convergence Technology)
Kim, Jun Kyeong (Safety Inspection for Infrastructure Laboratory, Advanced Institute of Convergence Technology)
Yeom, Min Kyo (Safety Inspection for Infrastructure Laboratory, Advanced Institute of Convergence Technology)
Kim, Jin Pyeong (Computer Vision & Artificial Intelligence Laboratory, Advanced Institute of Convergence Technology)
Publication Information
Journal of the Society of Disaster Information / v.17, no.2, 2021 , pp. 329-340 More about this Journal
Abstract
Purpose: In this paper, using artificial neural network algorithm, the Korean Peninsula was analyzed for drought vulnerable areas by predicting weather data changes. Method: Monthly cumulative precipitation data were utilized for research areas considering the specific nature areas, and weather data prediction through artificial neural network algorithm was carried out using statistical program R. The predicted data were applied to the Standardized Precipitation Index (SPI) to analyze drought vulnerable areas in the Korean Peninsula. Result: In this paper, the correlation coefficient values between real and predicted data are found to be 0.043879 higher on average than the regression results, using artificial neural network algorithms. Conclusion: The results of the research are expected to be used as basic research materials for responding to drought.
Keywords
Artificial Neural Network; Deep-Learning; Drought; Standardized Precipitation Index (SPI);
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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