首页|Researchers at Universitas Sebelas Maret Have Published New Data on Machine Lear ning (Leveraging machine learning for hydrological drought prediction and mitiga tion)
Researchers at Universitas Sebelas Maret Have Published New Data on Machine Lear ning (Leveraging machine learning for hydrological drought prediction and mitiga tion)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news reporting from the Universitas Sebelas Maret by NewsRx journalists, research stated, “Drought disasters have become a g lobal issue, occurring more frequently due to climate change and increasing wate r usage patterns.” The news editors obtained a quote from the research from Universitas Sebelas Mar et: “Adaptation and mitigation efforts to reduce disaster vulnerability involve effective drought monitoring, such as drought predictions. This study aims to pr edict the hydrological drought index (HDI) for the next 5 years (20242028) in th e Bendung Notog sub-watershed. The HDI prediction modeling is based on machine l earning with an artificial neural network (ANN) algorithm using historical HDI v alues from the past 20 years (2004-2023). The historical HDI was calculated usin g the Threshold Level Method with discharge data transformed by the NRECA method . The drought prediction model demonstrates high accuracy with performance asses sment values of MAE = 0.015, R = 0.91, R2 = 0.82, NSE = 0.82, and RMSE = 0.022. The HDI prediction results indicate that the Bendung Notog sub-watershed experie nces dry conditions annually during the dry season, with the lowest HDI and long est drought duration occurring in 2024.”
Universitas Sebelas MaretCyborgsEmer ging TechnologiesMachine Learning
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